@article {997, title = {Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning}, journal = {Medical Image Analysis}, volume = {94}, year = {2024}, pages = {103134}, abstract = {

Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters. In vivo and synthetic brain 5D-Diffusion-T1-T2*-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cram{\'e}r–Rao lower bound optimisation. The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value. The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.

}, keywords = {Brain, Diffusion-relaxation, Quantitative MRI, machine learning}, issn = {1361-8415}, doi = {https://doi.org/10.1016/j.media.2024.103134}, url = {https://www.sciencedirect.com/science/article/pii/S1361841524000598}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Maxime Descoteaux and Hugo Larochelle and Jana Hutter and Derek K. Jones and Chantal M.W. Tax} } @proceedings {990, title = {Assessing the variability of brain diffusion MRI preprocessing pipelines using a Region-of-Interest analysis}, volume = {5015}, year = {2023}, month = {2023}, abstract = {

The lack of a standardized preprocessing pipeline is a significant source of variability that might lower the reproducibility of studies, especially across sites and with incomplete description of the preprocessing workflows. We evaluate the downstream impact of variability in preprocessing workflow by quantifying the reproducibility and variability of region-of-interest (ROI) analyses. While many pipelines achieve excellent reproducibility in most ROI, we observed a large variability in performance of preprocessing workflows to the extent that some pipelines are detrimental to the data quality and reproducibility.

}, author = {Veraart, Jelle and Winzeck, Stephan and {\'A}lvaro Planchuelo-G{\'o}mez and Fricke, Bj{\"o}rn and Kornaropoulos, Evgenios N and Merisaari, Harri and Pieciak, Tomasz and Zou, Yukai and Descoteaux, Maxime} } @proceedings {988, title = {Comparison of data-driven and physics-informed learning approaches for optimising multi-contrast MRI acquisition protocols}, volume = {3701}, year = {2023}, month = {2023}, abstract = {

Multi-contrast MRI is used to assess the biological properties of tissues, but excessively long times are required to acquire high-quality datasets. To reduce acquisition time, physics-informed Machine Learning approaches were developed to select the optimal subset of measurements, decreasing the number of volumes by approximately 63\%, and predict the MRI signal and quantitative maps. These selection methods were compared to a full data-driven and two manual strategies. Synthetic and real 5D-Diffusion-T1-T2* data from five healthy participants were used. Feature selection via a combination of Machine Learning and physics modelling provides accurate estimation of quantitative parameters and prediction of MRI signal.

}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Descoteaux, Maxime and Aja-Fern{\'a}ndez, Santiago and Hutter, Jana and Jones, Derek K and Tax, Chantal M W} } @article {991, title = {HYDI-DSI revisited: constrained non-parametric EAP imaging without q-space re-gridding}, journal = {Medical Image Analysis}, volume = {84}, year = {2023}, month = {02/2023}, chapter = {102728}, abstract = {

Hybrid Diffusion Imaging (HYDI) was one of the first attempts to use multi-shell samplings of the q-space to infer diffusion properties beyond Diffusion Tensor Imaging (DTI) or High Angular ResolutionDiffusion Imaging (HARDI). HYDI was intended as a flexible protocol embedding both DTI (for lower b-values) and HARDI (for higher b-values) processing, as well as Diffusion Spectrum Imaging (DSI) when the entire data set was exploited. In the latter case, the spherical sampling of the q-space is re-gridded by interpolation to a Cartesian lattice whose extent covers the range of acquired b-values, hence being acquisition-dependent. The Discrete Fourier Transform (DFT) is afterwards used to compute the corresponding Cartesian sampling of the Ensemble Average Propagator (EAP) in an entirely non-parametric way. From this lattice, diffusion markers such as the Return To Origin Probability (RTOP) or the Mean Squared Displacement (MSD) can be numerically estimated.
We aim at re-formulating this scheme by means of a Fourier Transform encoding matrix that eliminates the need for q-space re-gridding at the same time it preserves the non-parametric nature of HYDI-DSI. The encoding matrix is adaptively designed at each voxel according to the underlying DTI approximation, so that an optimal sampling of the EAP can be pursued without being conditioned by the particular acquisition protocol. The estimation of the EAP is afterwards carried out as a regularized Quadratic Programming (QP) problem, which allows to impose positivity constraints that cannot be trivially embedded within the conventional HYDI-DSI. We demonstrate that the definition of the encoding matrix in the adaptive space allows to analytically (as opposed to numerically) compute several popular descriptors of diffusion with the unique source of error being the cropping of high frequency harmonics in the Fourier analysis of the attenuation signal. They include not only RTOP and MSD, but also Return to Axis/Plane Probabilities (RTAP/RTPP), which are defined in terms of specific spatial directions and are not available with the former HYDI-DSI. We report extensive experiments that suggest the benefits of our proposal in terms of accuracy, robustness and computational efficiency, especially when only standard, non-dedicated q-space samplings are available.

}, keywords = {Diffusion Spectrum Imaging, Ensemble Average Propagator, Hybrid Diffusion Imaging, diffusion MRI}, doi = {102728}, url = {https://www.sciencedirect.com/science/article/pii/S1361841522003565}, author = {Antonio Trist{\'a}n-Vega and Tomasz Pieciak and Guillem Par{\'\i}s and Justino R. Rodr{\'\i}guez-Galv{\'a}n and Santiago Aja-Fern{\'a}ndez} } @proceedings {989, title = {Impact of free-water correction on white matter changes measured by diffusion tensor imaging in migraine}, volume = {4601}, year = {2023}, month = {2023}, abstract = {

Menstrual migraine affects about 25\% of female migraine patients. However, the diagnosis of migraine is particularly difficult because the brain changes associated with migraine are challenging to detect with imaging techniques. Diffusion-weighted MRI (dMRI) permits the detection of alterations in the microenvironment of the brain tissues. We investigate whether removing the contribution of the free water component from the diffusion-signal can provide increased sensitivity to identify white matter changes in migraine using diffusion tensor metrics.

}, author = {Guadilla, Irene and Fouto, Ana and {\'A}lvaro Planchuelo-G{\'o}mez and Trist{\'a}n-Vega, Antonio and Ruiz-Tagle, Amparo and Esteves, In{\^e}s and Caetano, Gina and Silva, Nuno and Vilela, Pedro and Gil-Gouveia, Raquel and Aja-Fern{\'a}ndez, Santiago and Figueiredo, Patr{\'\i}cia and Nunes, Rita} } @article {994, title = {Increased MRI-based Brain Age in chronic migraine patients}, journal = {The Journal of Headache and Pain}, volume = {24}, year = {2023}, pages = {133}, abstract = {

Neuroimaging has revealed that migraine is linked to alterations in both the structure and function of the brain. However, the relationship of these changes with aging has not been studied in detail. Here we employ the Brain Age framework to analyze migraine, by building a machine-learning model that predicts age from neuroimaging data. We hypothesize that migraine patients will exhibit an increased Brain Age Gap (the difference between the predicted age and the chronological age) compared to healthy participants.

}, keywords = {Biomarkers, Brain age, machine learning, migraine disorders, neuroimaging}, issn = {1129-2377}, doi = {10.1186/s10194-023-01670-6}, url = {https://doi.org/10.1186/s10194-023-01670-6}, author = {Navarro-Gonz{\'a}lez, Rafael and Garc{\'\i}a-Azor{\'\i}n, David and Guerrero-Peral, {\'A}ngel L. and {\'A}lvaro Planchuelo-G{\'o}mez and Aja-Fern{\'a}ndez, Santiago and de Luis-Garc{\'\i}a, Rodrigo} } @proceedings {986, title = {Increased T1w MRI-based brain age in chronic migraine patients}, volume = {5327}, year = {2023}, month = {2023}, abstract = {

Brain-age is an emerging neuroimaging biomarker that represents the aging status of the brain using machine learning techniques from MRI data. It has been successfully applied to the study of different neurological and psychiatric conditions. We hypothesize that patients with migraine may show an increased brain age gap (difference between the age estimated from the MRI data and the chronological age). After building a brain age model from 2,781 healthy subjects, we tested this hypothesis on a dataset with 210 healthy controls and migraine patients. Results showed an increased brain age in chronic migraine patients with respect to healthy controls.

}, author = {Navarro-Gonz{\'a}lez, Rafael and Garc{\'\i}a-Azor{\'\i}n, David and Guerrero, {\'A}ngel L and {\'A}lvaro Planchuelo-G{\'o}mez and Aja-Fern{\'a}ndez, Santiago and de Luis-Garc{\'\i}a, Rodrigo} } @article {973, title = {Structural brain changes in patients with persistent headache after COVID-19 resolution}, journal = {Journal of Neurology}, volume = {270}, year = {2023}, pages = {13-31}, abstract = {

Headache is among the most frequently reported symptoms after resolution of COVID-19. We assessed structural brain changes using T1- and diffusion-weighted MRI processed data from 167 subjects: 40 patients who recovered from COVID-19 but suffered from persistent headache without prior history of headache (COV), 41 healthy controls, 43 patients with episodic migraine and 43 patients with chronic migraine. To evaluate gray matter and white matter changes, morphometry parameters and diffusion tensor imaging-based measures were employed, respectively. COV patients showed significant lower cortical gray matter volume and cortical thickness than healthy subjects (p\thinspace\<\thinspace0.05, false discovery rate corrected) in the inferior frontal and the fusiform cortex. Lower fractional anisotropy and higher radial diffusivity (p\thinspace\<\thinspace0.05, family-wise error corrected) were observed in COV patients compared to controls, mainly in the corpus callosum and left hemisphere. COV patients showed higher cortical volume and thickness than migraine patients in the cingulate and frontal gyri, paracentral lobule and superior temporal sulcus, lower volume in subcortical regions and lower curvature in the precuneus and cuneus. Lower diffusion metric values in COV patients compared to migraine were identified prominently in the right hemisphere. COV patients present diverse changes in the white matter and gray matter structure. White matter changes seem to be associated with impairment of fiber bundles. Besides, the gray matter changes and other white matter modifications such as axonal integrity loss seemed subtle and less pronounced than those detected in migraine, showing that persistent headache after COVID-19 resolution could be an intermediate state between normality and migraine.

}, issn = {1432-1459}, doi = {10.1007/s00415-022-11398-z}, url = {https://doi.org/10.1007/s00415-022-11398-z}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and Guerrero, {\'A}ngel L. and Rodr{\'\i}guez, Margarita and Aja-Fern{\'a}ndez, Santiago and de Luis-Garc{\'\i}a, Rodrigo} } @proceedings {987, title = {Super-resolution diffusion tensor imaging at 64 mT}, volume = {3624}, year = {2023}, month = {2023}, abstract = {

A super-resolution approach was used to create 2mm isotropic diffusion tensor images (DTI) from diffusion-weighted imaging data acquired on a low field, portable system. Mean diffusivity, fractional anisotropy and principal eigenvector orientation maps are shown. This work extends the very recently implemented capability of performing DTI on a 64mT system, and shows substantial improvement due to the increased through-plane resolution achieved with super-resolution.

}, author = {Plumley, Alix and Cercignani, Mara and {\'A}lvaro Planchuelo-G{\'o}mez and Gholam, James and Jones, Derek K} } @proceedings {984, title = {Tensors and Tracts at 64 mT}, volume = {104}, year = {2023}, month = {2023}, abstract = {

We present the first ever demonstration of Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) including quantitative measures of mean diffusivity, fractional anisotropy, and successful tractographic reconstruction of projection and commissural pathways on a portable system operating at 64 mT.

}, author = {Plumley, Alix and Padormo, Francesco and Cercignani, Mara and O{\textquoteright}Halloran, Rafael and Teixeira, Rui and {\'A}lvaro Planchuelo-G{\'o}mez and Legouhy, Antoine and Luo, Tianrui and Jones, Derek K} } @article {977, title = {Toward deep learning replacement of gadolinium in neuro-oncology: A review of contrast-enhanced synthetic MRI}, journal = {Frontiers in Neuroimaging}, volume = {2}, year = {2023}, issn = {2813-1193}, doi = {10.3389/fnimg.2023.1055463}, url = {https://www.frontiersin.org/articles/10.3389/fnimg.2023.1055463}, author = {Moya-S{\'a}ez, Elisa and de Luis-Garc{\'\i}a, Rodrigo and Alberola-L{\'o}pez, Carlos} } @proceedings {985, title = {Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies}, volume = {2786}, year = {2023}, month = {2023}, abstract = {

This work gathers the results of the QuadD22 challenge, held in MICCAI 2022. We evaluate whether Deep Learning (DL) Techniques are able to improve the quality of diffusion MRI data in clinical studies. To that end, we focused on a real study on migraine, where the differences between groups are drastically reduced when using 21 gradient directions instead of 61. Thus, we asked the participants to augment dMRI data acquired with only 21 directions to 61 via DL. The results were evaluated using a real clinical study with TBSS in which we statistically compared episodic migraine to chronic migraine.

}, author = {Aja-Fernandez, Santiago and Martin-Martin, Carmen and Pieciak, Tomasz and {\'A}lvaro Planchuelo-G{\'o}mez and Faiyaz, Abrar and Uddin, Nasir and Tiwari, Abhishek and Shigwan, Saurabh J and Zheng, Tianshu and Cao, Zuozhen and Blumberg, Stefano B and Sen, Snigdha and Yigit Avci, Mehmet and Li, Zihan and Wang, Xinyi and Tang, Zihao and Rauland, Amelie and Merhof, Dorit and Manzano Maria, Renata and Campos, Vinicius P and HashemiazadehKolowri, SeyyedKazem and DiBella, Edward and Peng, Chenxu and Chen, Zan and Ullah, Irfan and Mani, Merry and Eckstrom, Samuel and Baete, Steven H and Scifitto, Scifitto and Singh, Rajeev Kumar and Wu, Dan and Goodwin-Allcock, Tobias and Slator, Paddy J and Bilgic, Berkin and Tian, Qiyuan and Cabezas, Mariano and Santini, Tales and Andrade da Costa Vieira, Marcelo and Shen, Zhimin and Abdolmotalleby, Hesam and Filipiak, Patryk and Tristan-Vega, Antonio and de Luis-Garcia, Rodrigo} } @article {995, title = {Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies}, journal = {NeuroImage: Clinical}, volume = {39}, year = {2023}, pages = {103483}, abstract = {

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise.

}, keywords = {Angular resolution, Artificial Intelligence, Deep learning, Diffusion tensor, diffusion MRI, machine learning}, issn = {2213-1582}, doi = {https://doi.org/10.1016/j.nicl.2023.103483}, url = {https://www.sciencedirect.com/science/article/pii/S2213158223001742}, author = {Santiago Aja-Fern{\'a}ndez and Carmen Mart{\'\i}n-Mart{\'\i}n and {\'A}lvaro Planchuelo-G{\'o}mez and Abrar Faiyaz and Md Nasir Uddin and Giovanni Schifitto and Abhishek Tiwari and Saurabh J. Shigwan and Rajeev Kumar Singh and Tianshu Zheng and Zuozhen Cao and Dan Wu and Stefano B. Blumberg and Snigdha Sen and Tobias Goodwin-Allcock and Paddy J. Slator and Mehmet Yigit Avci and Zihan Li and Berkin Bilgic and Qiyuan Tian and Xinyi Wang and Zihao Tang and Mariano Cabezas and Amelie Rauland and Dorit Merhof and Renata Manzano Maria and Vin{\'\i}cius Paran{\'\i}ba Campos and Tales Santini and Marcelo Andrade da Costa Vieira and SeyyedKazem HashemizadehKolowri and Edward DiBella and Chenxu Peng and Zhimin Shen and Zan Chen and Irfan Ullah and Merry Mani and Hesam Abdolmotalleby and Samuel Eckstrom and Steven H. Baete and Patryk Filipiak and Tanxin Dong and Qiuyun Fan and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Tomasz Pieciak} } @article {980, title = {Viability of AMURA biomarkers from single-shell diffusion MRI in clinical studies}, journal = {Frontiers in Neuroscience}, volume = {17}, year = {2023}, pages = {1106350}, abstract = {

Diffusion Tensor Imaging (DTI) is the most employed method to assess white matter properties using quantitative parameters derived from diffusion MRI, but it presents known limitations that restrict the evaluation of complex structures. The objective of this study was to validate the reliability and robustness of complementary diffusion measures extracted with a novel approach, Apparent Measures Using Reduced Acquisitions (AMURA), with a typical diffusion MRI acquisition from a clinical context in comparison with DTI with application to clinical studies. Fifty healthy controls, 51 episodic migraine and 56 chronic migraine patients underwent single-shell diffusion MRI. Four DTI-based and eight AMURA-based parameters were compared between groups with tract-based spatial statistics to establish reference results. On the other hand, following a region-based analysis, the measures were assessed for multiple subsamples with diverse reduced sample sizes and their stability was evaluated with the coefficient of quartile variation. To assess the discrimination power of the diffusion measures, we repeated the statistical comparisons with a region-based analysis employing reduced sample sizes with diverse subsets, decreasing 10 subjects per group for consecutive reductions, and using 5,001 different random subsamples. For each sample size, the stability of the diffusion descriptors was evaluated with the coefficient of quartile variation. AMURA measures showed a greater number of statistically significant differences in the reference comparisons between episodic migraine patients and controls compared to DTI. In contrast, a higher number of differences was found with DTI parameters compared to AMURA in the comparisons between both migraine groups. Regarding the assessments reducing the sample size, the AMURA parameters showed a more stable behavior than DTI, showing a lower decrease for each reduced sample size or a higher number of regions with significant differences. However, most AMURA parameters showed lower stability in relation to higher coefficient of quartile variation values than the DTI descriptors, although two AMURA measures showed similar values to DTI. For the synthetic signals, there were AMURA measures with similar quantification to DTI, while other showed similar behavior. These findings suggest that AMURA presents favorable characteristics to identify differences of specific microstructural properties between clinical groups in regions with complex fiber architecture and lower dependency on the sample size or assessing technique than DTI.

}, issn = {1662-453X}, doi = {10.3389/fnins.2023.1106350}, url = {https://www.frontiersin.org/articles/10.3389/fnins.2023.1106350}, author = {Mart{\'\i}n-Mart{\'\i}n, Carmen and {\'A}lvaro Planchuelo-G{\'o}mez and Guerrero, {\'A}ngel L. and Garc{\'\i}a-Azor{\'\i}n, David and Trist{\'a}n-Vega, Antonio and de Luis-Garc{\'\i}a, Rodrigo and Aja-Fern{\'a}ndez, Santiago} } @article {956, title = {Anisotropy measure from three diffusion-encoding gradient directions}, journal = {Magnetic Resonance Imaging}, volume = {88}, year = {2022}, month = {2022}, pages = {38{\textendash}43}, author = {Santiago Aja-Fern{\'a}ndez and Guillem Par{\'\i}s and Carmen Mart{\'\i}n-Mart{\'\i}n and Derek K. Jones and AntonioTrist{\'a}n-Vega} } @conference {975, title = {Comparing signal models for correcting diffusion-weighted MR images for free water partial volume effects}, booktitle = {ISMRM Workshop on Diffusion MRI: From Research to Clinic}, year = {2022}, address = {Amsterdam, The Netherlands}, author = {Guadilla, Irene and Fouto, Ana R. and {\'A}lvaro Planchuelo-G{\'o}mez and Trist{\'a}n-Vega, Antonio and Ruiz-Tagle, Amparo and Esteves, In{\^e}s and Caetano, Gina and Aja-Fern{\'a}ndez, Santiago and Figueiredo, Patr{\'\i}cia and Nunes, Rita G.} } @conference {974, title = {Data-driven and physics-informed learning of efficient acquisition protocols}, booktitle = {ISMRM Workshop on Diffusion MRI: From Research to Clinic}, year = {2022}, address = {Amsterdam, The Netherlands}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Descoteaux, Maxime and Aja-Fern{\'a}ndez, Santiago and Hutter, Jana and Jones, Derek K. and Tax, Chantal M.W.} } @article {964, title = {Default mode network components and its relationship with anomalous self-experiences in schizophrenia: A rs-fMRI exploratory study}, journal = {Psychiatry Research: Neuroimaging}, volume = {324}, year = {2022}, pages = {111495}, abstract = {

Anomalous self-experiences (ASEs) in schizophrenia have been under research for the last 20 years. However, no neuroimage studies have provided insight of the possible biological underpinning of ASEs. In this novel approach, the connectivity within the default mode network, calculated through a ROI-based analysis of functional magnetic resonance imaging data, was correlated to the ASEs scores assessed by the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE) in a sample of 22 schizophrenia patients. The Pearson{\textquoteright}s correlation coefficients between IPASE scores and intrahemispheric connectivity of the parahippocampal gyrus with the isthmus cingulate cortex in both hemispheres, and right parahippocampal gyrus with the right rostral anterior cingulate cortex were positive and significant suggesting a relation between hyperactive functional connectivity and anomalous self-experiences intensity. Prior literature reported these areas to have a role in self-processing and consciousness as well as being anatomically connected. Further research with larger sample size and comparison with controls are needed to confirm the relationship of this connectivity with anomalous self-experiences.

}, keywords = {Anterior cingulate cortex, Metacognition, Parahippocampal gyrus, Psychosis, functional magnetic resonance imaging}, issn = {0925-4927}, doi = {https://doi.org/10.1016/j.pscychresns.2022.111495}, url = {https://www.sciencedirect.com/science/article/pii/S0925492722000567}, author = {Roig-Herrero, Alejandro and {\'A}lvaro Planchuelo-G{\'o}mez and Hern{\'a}ndez-Garc{\'\i}a, Marta and de Luis-Garc{\'\i}a, Rodrigo and Fern{\'a}ndez-Linsenbarth, In{\'e}s and Be{\~n}o-Ruiz-de-la-Sierra, Rosa M. and Molina, Vicente} } @conference {968, title = {Long-term grey matter structural changes in the transition from chronic migraine to episodic migraine}, booktitle = {8th Congress of the European Academy of Neurology}, year = {2022}, month = {2022}, abstract = {

Background and aims: The objective was to assess grey matter longitudinal changes in patients with chronic migraine (CM) who reverse to episodic migraine (EM) compared to those who do not reverse.

Methods: High-resolution 3D brain T1-weighted Magnetic Resonance Imaging data were obtained twice from migraine patients. The first acquisition was performed immediately after the first visit to the Headache Unit, before taking preventive treatments. The second timepoint was at least three years after the first acquisition. From the longitudinal pipeline of FreeSurfer (v6.0), the mean values of cortical thickness, surface area and grey matter volume of 68 cortical, 14 subcortical regions and the cerebellum were extracted. Longitudinal changes between patients with CM and those who reversed to EM were assessed with linear
mixed-effects models, setting p\<0.05 (false discovery rate corrected) as threshold for statistical significance.

Results: 22 patients were included, and 10 of them (45.5\%) reversed to EM. No statistically significant differences of age (42.0+-9.0 years) and sex (21 women, 95.5\%) were found between patient groups. Higher statistically significant values of the three parameters in patients who reversed to EM were found in the pericalcarine, parietal, orbitofrontal cortex, and amygdala (Table 1, Figure 1). In contrast, lower values were detected in the cingulum, caudal middle frontal cortex, cerebellum, caudate nucleus and pallidum (Figure 2). In the insula, higher thickness but lower area was appreciated in patients who reversed.

Conclusion: Patients with CM who reverse to EM present distinct patterns of increased and decreased morphometric parameters propagated in the orbital frontal cortex and the cingulum, respectively.

Disclosure: Nothing to disclose.

}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Marchante-Re{\'\i}llo, Ginebra and Sierra, {\'A}lvaro and Garc{\'\i}a-Azor{\'\i}n, David and Mart{\'\i}n-Mart{\'\i}n, Carmen and de Luis-Garc{\'\i}a, Rodrigo and Aja-Fern{\'a}ndez, Santiago and Moro, Ra{\'u}l and Rodr{\'\i}guez, Margarita and Gonz{\'a}lez-Osorio, Y{\'e}sica and {\'A}ngel L. Guerrero} } @article {954, title = {Moment-based representation of the diffusion inside the brain from reduced DMRI acquisitions: Generalized AMURA}, journal = {Medical Image Analysis}, volume = {77}, year = {2022}, pages = {102356}, abstract = {

AMURA (Apparent Measures Using Reduced Acquisitions) was originally proposed as a method to infer micro-structural information from single-shell acquisitions in diffusion MRI. It reduces the number of samples needed and the computational complexity of the estimation of diffusion properties of tissues by assuming the diffusion anisotropy is roughly independent on the b-value. This simplification allows the computation of simplified expressions and makes it compatible with standard acquisition protocols commonly used even in clinical practice. The present work proposes an extension of AMURA that allows the calculation of general moments of the diffusion signals that can be applied to describe the diffusion process with higher accuracy. We provide simplified expressions to analytically compute a set of scalar indices as moments of arbitrary orders over either the whole 3-D space, particular directions, or particular planes. The existing metrics previously proposed for AMURA (RTOP, RTPP and RTAP) are now special cases of this generalization. An extensive set of experiments is performed on public data and a clinical clase acquired with a standard type acquisition. The new metrics provide additional information about the diffusion processes inside the brain.

}, keywords = {AMURA, Diffusion anisotropy, Fast acquisition, diffusion MRI, white matter}, issn = {1361-8415}, doi = {https://doi.org/10.1016/j.media.2022.102356}, url = {https://www.sciencedirect.com/science/article/pii/S1361841522000093}, author = {Aja-Fern{\'a}ndez, Santiago and Pieciak, Tomasz and Mart{\'\i}n-Mart{\'\i}n, Carmen and {\'A}lvaro Planchuelo-G{\'o}mez and de Luis-Garc{\'\i}a, Rodrigo and Trist{\'a}n-Vega, Antonio} } @conference {967, title = {Objective measurement of pain related to cardiac surgery: a study using algometry}, booktitle = {8th Congress of the European Academy of Neurology}, year = {2022}, month = {2022}, abstract = {

Background and aims: Algometry is a safe and objective technique to quantify pain, up to now used in headache research, but to a lesser extent to assess pain related to surgery. We aimed to analyze the demographic characteristics of pain related to cardiac surgery, assessed using static algometry.

Methods: Adult patients consecutively undergoing cardiac surgery were prospectively recruited. Pressure pain thresholds (PPT) were measured in both sides of sternum manubrium, body (five measures) and xiphoid process, preoperatively and on days 1, 3 and 7 postoperatively. Linear mixed-effects models were employed to assess the longitudinal changes and results were corrected for multiple comparisons following a false discovery rate procedure.

Results: We included 70 patients (41.4\% female) with a median age of 67.5 years (range 26-85). Regarding the baseline values, PPT were significantly lower in women and patients older than 65 years. After the surgery, there was a significant reduction of PPT in all assessed regions, which was partially compensated after seven days. Moreover, postoperatively, differences associated with age disappeared and those associated with sex were almost negligible. These differences related to age and sex increased after seven days of surgery, but this difference was lower in comparison with the baseline situation (Table 1, Figure 1). Postoperative pain perception was significantly higher (lower PPT) in both sexes.

Conclusion: Pain related to cardiac surgery can be measured with algometry, mainly during first postoperative days. Differences in pain sensitivity related to age and sex decrease after surgery.

Disclosure: No conflict of interest.

}, author = {Segura-M{\'e}ndez, B{\'a}rbara and {\'A}lvaro Planchuelo-G{\'o}mez and Sierra, {\'A}lvaro and Garc{\'\i}a-Azor{\'\i}n, David and Velasco-Garc{\'\i}a, E. and Fuentes-Mart{\'\i}n, {\'A}. and S{\'a}nchez, C. and V{\'a}zquez-Alarc{\'o}n de la Lastra, I. and {\'A}ngel L. Guerrero and Carrascal, Yolanda} } @article {957, title = {Perceived quality of life (QOLIE-31-P), depression (NDDI-E), anxiety (GAD-7), and insomnia in patients with epilepsy attended at a refractory epilepsy unit in real-life clinical practice}, journal = {Neurological Sciences}, volume = {43}, year = {2022}, month = {2022}, pages = {1955-1964}, doi = {https://doi.org/10.1007/s10072-021-05595-3}, url = {https://link.springer.com/article/10.1007/s10072-021-05595-3}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira Campos, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo-Heras, Mar{\'\i}a} } @article {963, title = {Synthetic MRI improves radiomics-based glioblastoma survival prediction}, journal = {NMR in Biomedicine}, year = {2022}, chapter = {e4754}, doi = {10.1002/nbm.4754}, author = {Elisa Moya-S{\'a}ez and Rafael Navarro-Gonz{\'a}lez and Santiago Cepeda and {\'A}ngel P{\'e}rez-N{\'u}{\~n}ez and Rodrigo de Luis-Garcia and Santiago Aja-Fernández and Carlos Alberola-L{\'o}pez} } @conference {976, title = {Tensors and Tracts at 64 mT}, booktitle = {ISMRM Workshop on Diffusion MRI: From Research to Clinic}, year = {2022}, address = {Amsterdam, The Netherlands}, author = {Plumley, Alix and Padormo, Francesco and Cercignani, Mara and O{\textquoteright}Halloran, Rafael and Teixeira, Rui and {\'A}lvaro Planchuelo-G{\'o}mez and Legouhy, Antoine and Luo, Tianrui and Jones, Derek K.} } @article {934, title = {Accurate free-water estimation in white matter from fast diffusion MRI acquisitions using the spherical means technique}, journal = {Magnetic Resonance in Medicine}, volume = {87}, year = {2021}, month = {2022}, pages = {1028-1035}, type = {Techncial Note}, abstract = {

Purpose To accurately estimate the partial volume fraction of free water in the white matter from diffusion MRI acquisitions not demanding strong sensitizing gradients and/or large collections of different b-values. Data sets considered comprise 32-64 gradients near plus 6 gradients near . Theory and Methods The spherical means of each diffusion MRI set with the same b-value are computed. These means are related to the inherent diffusion parameters within the voxel (free- and cellular-water fractions; cellular-water diffusivity), which are solved by constrained nonlinear least squares regression. Results The proposed method outperforms those based on mixtures of two Gaussians for the kind of data sets considered. W.r.t. the accuracy, the former does not introduce significant biases in the scenarios of interest, while the latter can reach a bias of 5\%{\textendash}7\% if fiber crossings are present. W.r.t. the precision, a variance near , compared to 15\%, can be attained for usual configurations. Conclusion It is possible to compute reliable estimates of the free-water fraction inside the white matter by complementing typical DTI acquisitions with few gradients at a lowb-value. It can be done voxel-by-voxel, without imposing spatial regularity constraints.

}, keywords = {diffusion MRI, free water, spherical means, white matter}, doi = {https://doi.org/10.1002/mrm.28997}, author = {Antonio Trist{\'a}n-Vega and Guillem Par{\'\i}s and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez} } @article {899, title = {Apparent propagator anisotropy from single-shell diffusion MRI acquisitions}, journal = {Magnetic Resonance in Medicine}, volume = {85}, year = {2021}, month = {2021}, pages = {2869-2881}, chapter = {2869}, doi = {https://doi.org/10.1002/mrm.28620}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28620}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Derek K. Jones} } @conference {941, title = {Clinical course of migraine during the COVID-19 Lockdown}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: Previous studies have demonstrated that migraine can worsen due to stress, changes in lifestyle habits or infections. We hypothesize that changes during coronavirus disease 2019 (COVID-19) lockdown might have worsened the clinical course of migraine.
Methods: Retrospective survey study collecting demographic data, clinical variables related to headache (frequency), migraine (subjective worsening, frequency, and intensity), lockdown, and symptoms of post-traumatic stress from migraine patients followed-up at three Headache Units between June-July 2020.
Results: 222 subjects were included. Among them, 201/222 (90.5\%) were women, aged 42.5 +- 12.0 (mean +- SD). Subjective improvement of migraine was reported in 31/222 participants (14.0\%), while worsening in 105/222 (47.3\%) and was associated with changes in migraine triggers such as stress related to going outdoors and intake of specific foods/drinks. Intensity of attacks increased in 67/222 patients (30.2\%), and it was associated with the subjective worsening, female sex, recent insomnia, and use of acute medication during a headache. An increase in monthly days with any headache was observed in 105/222 patients (47.3\%) and was related to symptoms of post-traumatic stress, older age and living with five or more people.

Conclusion: Approximately half the migraine patients reported worsening of their usual pain during the lockdown; worsening was related to changes in triggers and the emotional impact of the lockdown.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and P{\'e}rez-Navarro, Mar{\'\i}a P and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and Rodrigo de Luis-Garc{\'\i}a and Ana B Gago-Veiga} } @article {925, title = {A Clinically Viable Vendor-Independent and Device-Agnostic Solution for Accelerated Cardiac MRI Reconstruction}, journal = {Computer Methods and Programs in Biomedicine}, volume = {207}, year = {2021}, chapter = {106143}, issn = {0169-2607}, doi = {https://doi.org/10.1016/j.cmpb.2021.106143}, url = {https://www.sciencedirect.com/science/article/pii/S0169260721002182}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Elisa Moya-S{\'a}ez and Mench{\'o}n-Lara, Rosa-Mar{\'\i}a and J Royuela-del-Val and Palencia-de-Lara, C{\'e}sar and M. Rodr{\'\i}guez-Cayetano and Simmross-Wattenberg, Federico and Carlos Alberola-Lopez} } @article {952, title = {Effects of the onabotulinumtoxinA follow-up delay in migraine course during the COVID-19 lockdown}, journal = {Neurological Sciences}, volume = {42}, year = {2021}, pages = {5087-5092}, issn = {1590-3478}, doi = {10.1007/s10072-021-05180-8}, url = {https://doi.org/10.1007/s10072-021-05180-8}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a Pilar and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and de Luis-Garc{\'\i}a, Rodrigo and Ana B Gago-Veiga} } @article {900, title = {Efficient and accurate EAP imaging from multi-shell dMRI with Micro-Structure adaptive convolution kernels and dual Fourier Integral Transforms (MiSFIT)}, journal = {NeuroImage}, volume = {227}, year = {2021}, month = {2021}, pages = {117616}, issn = {1053-8119}, doi = {https://doi.org/10.1016/j.neuroimage.2020.117616}, url = {http://www.sciencedirect.com/science/article/pii/S1053811920311010}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @article {920, title = {Elastic AlignedSENSE for Dynamic MR Reconstruction: A Proof of Concept in Cardiac Cine}, journal = {Entropy}, volume = {23}, year = {2021}, pages = {555}, abstract = {

Numerous methods in the extensive literature on magnetic resonance imaging (MRI) reconstruction exploit temporal redundancy to accelerate cardiac cine. Some of them include motion compensation, which involves high computational costs and long runtimes. In this work, we proposed a method {\textendash}-elastic alignedSENSE (EAS){\textendash}- for the direct reconstruction of a motion-free image plus a set of nonrigid deformations to reconstruct a 2D cardiac sequence. The feasibility of the proposed approach was tested in 2D Cartesian and golden radial multi-coil breath-hold cardiac cine acquisitions. The proposed approach was compared against parallel imaging compressed sense (sPICS) and group-wise motion corrected compressed sense (GWCS) reconstructions. EAS provides better results on objective measures with considerable less runtime when an acceleration factor is higher than 10x. Subjective assessment of an expert, however, invited proposing the combination of EAS and GWCS as a preferable alternative to GWCS or EAS in isolation.

}, issn = {1099-4300}, doi = {10.3390/e23050555}, url = {https://www.mdpi.com/1099-4300/23/5/555}, author = {Alejandro Godino-Moya and Mench{\'o}n-Lara, Rosa-Mar{\'\i}a and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Prieto, Claudia and Alberola-L{\'o}pez, Carlos} } @article {944, title = {Evaluation of the Impact of the COVID-19 Lockdown in the Clinical Course of Migraine}, journal = {Pain Medicine}, volume = {22}, year = {2021}, month = {2021}, pages = {2079-2091}, abstract = {

Objective: Previous studies have demonstrated that emotional stress, changes in lifestyle habits and infections can worsen the clinical course of migraine. We hypothesize that changes in habits and medical care during coronavirus disease 2019 (COVID-19) lockdown might have worsened the clinical course of migraine.

Design: Retrospective survey study collecting online responses from migraine patients followed-up by neurologists at three tertiary hospitals between June and July 2020.

Methods: We used a web-based survey that included demographic data, clinical variables related with any headache (frequency) and migraine (subjective worsening, frequency, and intensity), lockdown, and symptoms of post-traumatic stress.

Results: The response rate of the survey was 239/324 (73.8\%). The final analysis included 222 subjects. Among them, 201/222 (90.5\%) were women, aged 42.5 +- 12.0 (mean+-SD). Subjective improvement of migraine during lockdown was reported in 31/222 participants (14.0\%), while worsening in 105/222 (47.3\%) and was associated with changes in migraine triggers such as stress related to going outdoors and intake of specific foods or drinks. Intensity of attacks increased in 67/222 patients (30.2\%), and it was associated with the subjective worsening, female sex, recent insomnia, and use of acute medication during a headache. An increase in monthly days with any headache was observed in 105/222 patients (47.3\%) and was related to symptoms of post-traumatic stress, older age and living with five or more people.

Conclusions: Approximately half the migraine patients reported worsening of their usual pain during the lockdown. Worse clinical course in migraine patients was related to changes in triggers and the emotional impact of the lockdown.

}, keywords = {COVID-19, Headache, Lockdown, Migraine, SARS-CoV-2}, issn = {1526-4637}, doi = {10.1093/pm/pnaa449}, url = {https://doi.org/10.1093/pm/pnaa449}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a Pilar and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and Rodrigo de Luis-Garc{\'\i}a and Ana B Gago-Veiga} } @conference {940, title = {Evaluation of the burden of migraine on the partners lifestyle: a multicenter study}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: Migraine is a highly disabling disease that affects the patient{\textquoteright}s life, but its consequences on the patient{\textquoteright}s partner have been barely studied. The objective was to analyze these effects on romantic relationship, relationship with their children, friendship and work; as well as to evaluate caregiver burden and the presence of anxiety and/or depression.
Methods: Cross-sectional observational study. An online survey was filled by partners of migraine patients from five Spanish Headache Units. Questions about the four assessed areas and two scales to evaluate anxiety, depression and caregiver burden (Hospital Anxiety and Depression Scale and Zarit scale) were included. The presence of anxiety and depression was compared to the Spanish prevalence (6.7\% in both cases).
Results: Out of 176 registered responses, 155 were accepted. The sample included 86.5\% of women, with mean age 44.2 +- 10.4 years. Effects on partners were found on love relationship and items concerning children and friendships, with a minor impact at work. Partners showed a significant moderate burden according to the Zarit scale (p = 12/155 = 0.077 [0.041-0.131]; p \< 0.001) and a higher anxiety rate than the 6.7\% national prevalence (p = 23/155 = 0.148 [0.096-0.214]; p \< 0.001), but similar depression rate.
Conclusion: We found an impact on the patient{\textquoteright}s partners on the studied areas. Migraine is a disease that implies caregiver burden in the patient{\textquoteright}s environment with possible effect on anxiety levels.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {Fern{\'a}ndez-Bermejo, Eva M and {\'A}lvaro Planchuelo-G{\'o}mez and Quintas, Sonia and Gonzalez-Martinez, Alicia and Garc{\'\i}a-Azor{\'\i}n, David and Sierra, {\'A}lvaro and {\'A}ngel L. Guerrero and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a P and Gonz{\'a}lez-Garc{\'\i}a, Nuria and D{\'\i}az-de-Ter{\'a}n, Javier and Ana B Gago-Veiga} } @article {960, title = {Fast 4D elastic group-wise image registration. Convolutional interpolation revisited}, journal = {Computer Methods and Programs in Biomedicine}, volume = {200}, year = {2021}, pages = {105812}, abstract = {

Background and Objective:This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm. Methods:Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients. Results:The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90\%, both in CPU and GPU executions, compared with the classical tensor product formulation. Conclusions:Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.

}, keywords = {B-splines, Convolution, Efficient implementation, Free-form deformation, Groupwise Registration, Non-rigid registration}, issn = {0169-2607}, doi = {https://doi.org/10.1016/j.cmpb.2020.105812}, url = {https://www.sciencedirect.com/science/article/pii/S016926072031645X}, author = {Rosa-Mar{\'\i}a Mench{\'o}n-Lara and Javier Royuela-del-Val and Federico Simmross-Wattenberg and Pablo Casaseca-de-la-Higuera and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-L{\'o}pez} } @conference {937, title = {Gray matter cortical changes in patients with persistent headache after COVID-19 infection: an exploratory study}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: To evaluate gray matter alterations in patients with persistent headache after COVID-19 resolution.
Methods: Exploratory case-control study. Highresolution 3D brain T1-weighted Magnetic Resonance Imaging data were acquired in patients with persistent
headache after COVID-19 infection and healthy controls (HC). FreeSurfer (version 6.0) was employed to segment the T1-weighted images and extract the mean values of the cortical curvature (CC) and thickness (CT), surface area (SA) and gray matter volume (GMV) of 68 cortical regions. GMV comparisons were adjusted for intracranial volume. Significant results were considered with p \< 0.05 (False Discovery Rate corrected).
Results: Ten patients with persistent headache after COVID-19 (mean age: 53.8 +- 7.8 years; nine women) and 10 HC balanced for age and sex (mean age: 53.1 +- 7.0 years; nine women) were included in the study. Significant higher mean SA and GMV values were found in patients with persistent headache compared to HC in the bilateral medial orbitofrontal cortex, left rostral middle frontal gyrus, and right pars opercularis and superior frontal gyrus. In the patients, significant higher GMV in the right caudal anterior cingulate gyrus and SA values in five temporal, frontal and parietal regions were observed. No CC or CT changes were found.
Conclusions: Persistent headache after COVID-19 infection is related to gray matter cortical changes defined by higher GMV and SA values mainly localized in frontal regions.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Moro, Ra{\'u}l and Rodrigo de Luis-Garc{\'\i}a} } @conference {942, title = {Has onabotulinumtoxinA follow-up delay during COVID-19 lockdown affected the migraine course?}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: During the COVID-19 pandemic face-to-face procedures have been postponed. We aim to evaluate the impact of onabotulinumtoxinA follow-up delay in migraine during COVID-19 pandemic.
Methods: Subjective worsening, intensity of migraine attacks and frequency of headache and migraine were retrospectively compared between patients with unmodified and interrupted onabotulinumtoxinA follow-up in Headache Units.
Results: We included 67 patients with chronic migraine or high-frequency episodic migraine under onabotulinumtoxinA treatment, 65 (97.0\%) female,
44.5 +- 12.1 years old. Treatment administration was voluntarily delayed in 14 (20.9\%) patients and nine (13.4\%) were unable to continue follow-up. Patients with uninterrupted follow-up during lockdown presented 8.4 and 8.1 less monthly days with headache (adjusted p = 0.011) and migraine attacks (adjusted p = 0.009) compared to patients whose follow-up was interrupted, respectively.
Conclusion: Involuntary delay of onabotulinumtoxinA follow-up in patients with migraine due to COVID-19 pandemic was associated with a higher frequency of headache and migraine attacks. Safe administration of onabotulinumtoxinA during lockdown should be promoted.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David and Santos-Lasaosa, Sonia and Navarro-P{\'e}rez, Mar{\'\i}a P and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Quintas, Sonia and Rodrigo de Luis-Garc{\'\i}a and Ana B Gago-Veiga} } @conference {945, title = {Longitudinal reduction of quality of life in patients with epilepsy and no seizure increase during the COVID-19 pandemic}, booktitle = {7th Congress of the European Academy of Neurology}, year = {2021}, month = {2021}, publisher = {Wiley}, organization = {Wiley}, address = {Virtual Congress}, abstract = {

Background and aims: In early 2020, the novel coronavirus disease (COVID-19) pandemic has impaired medical care of chronic neurological diseases, including epilepsy. The objective of this study is to evaluate the impact of the COVID-19 pandemic in the levels of anxiety, depression, somnolence and quality of life using validated scales in patients with epilepsy in real-life clinical practice.
Methods: Self-administered scales of anxiety disorders (GAD-7), depression (NDDI-E), somnolence (Epworth Sleepiness Scale; ESS) and quality of life (QOLIE-31-P) in patients with epilepsy treated in the Refractory Epilepsy Unit of a tertiary hospital were longitudinally analyzed with Generalized Linear Mixed Models. Data were collected before the beginning (December 2019-March 2020) and during the COVID-19 pandemic (September 2020-January 2021).
Results: 37 patients, 45.0+-17.3 years of age, 43.2\% women, epilepsy duration 23.0+-14.9 years, number of anti-epileptic drugs 2.1+-1.4, answered in the two periods. Significant longitudinal reduction of QOLIE-31-P scores (from 58.9+-19.7 to 56.2+-16.2, p=0.035) was identified. No statistically significant longitudinal changes in NDDI-E (from 12.3+-4.3 to 13.4+-4.4, p=0.293) or the number of seizures (from 0.9+-1.9 to 2.5+-6.2, p=0.125) were found. Significant higher ESS (from 4.9+-3.7 to 7.4+-4.9, p=0.001) and lower GAD-7 scores (from 8.8+-6.2 to 8.3+-5.9, corrected p=0.024 adjusted by refractory epilepsy and sleep disturbance) were found during the COVID-19 pandemic.
Conclusion: During the COVID-19 pandemic, quality of life was lower in patients with epilepsy, levels of anxiety were reduced and sleepiness levels were raised, without seizure change. Additional studies would be useful to adequately manage these comorbidities.
Disclosure: There is no disclosure.

}, url = {https://www.ean.org/fileadmin/user_upload/ean/congress-2021/EAN2021AbstractBook.pdf}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo, Mar{\'\i}a} } @article {947, title = {Magnetic Resonance Simulation in Education: Quantitative Evaluation of an Actual Classroom Experience}, journal = {Sensors}, volume = {21}, year = {2021}, pages = {6011}, abstract = {

Magnetic resonance is an imaging modality that implies a high complexity for radiographers. Despite some simulators having been developed for training purposes, we are not aware of any attempt to quantitatively measure their educational performance. The present study gives an answer to the question: Does an MRI simulator built on specific functional and non-functional requirements help radiographers learn MRI theoretical and practical concepts better than traditional educational method based on lectures? Our study was carried out in a single day by a total of 60 students of a main hospital in Madrid, Spain. The experiment followed a randomized pre-test post-test design with a control group that used a traditional educational method, and an experimental group that used our simulator. Knowledge level was assessed by means of an instrument with evidence of validity in its format and content, while its reliability was analyzed after the experiment. Statistical differences between both groups were measured. Significant statistical differences were found in favor of the participants who used the simulator for both the post-test score and the gain (difference between post-test and pre-test scores). The effect size turned out to be significant as well. In this work we evaluated a magnetic resonance simulation paradigm as a tool to help in the training of radiographers. The study shows that a simulator built on specific design requirements is a valuable complement to traditional education procedures, backed up with significant quantitative results.

}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Matute-Teresa, F{\'a}tima and Bote-Lorenzo, Miguel L and G{\'o}mez-S{\'a}nchez, Eduardo and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {943, title = {Medium-term changes in patients with epilepsy during the COVID-19 pandemic}, journal = {Acta Neurologica Scandinavica}, volume = {144}, year = {2021}, pages = {450-459}, abstract = {

Objectives: The novel coronavirus disease (COVID-19) pandemic has led to social distancing measures and impaired medical care of chronic neurological diseases, including epilepsy, which may have adversely affected well-being and quality of life of patients with epilepsy (PWE). The objective of this study is to evaluate the impact of the COVID-19 pandemic in the levels of anxiety, depression, somnolence, and quality of life using validated scales in PWE in real-life clinical practice.

Materials \& Methods: Self-administered scales of anxiety disorders (GAD-7), depression (NDDI-E), somnolence (Epworth Sleepiness Scale; ESS), and quality of life (QOLIE-31-P) in PWE treated in a Refractory Epilepsy Unit were longitudinally analyzed. Data were collected before the beginning (December 2019-March 2020) and during the COVID-19 pandemic (September 2020-January 2021).

Results: 158 patients (85 from the first round and 73 from the second round) 45.0 +- 17.3 years of age, 43.2\% women, epilepsy duration 23.0 +- 14.9 years, number of antiepileptic drugs 2.1 +- 1.4, completed the survey. Significant longitudinal reduction of QOLIE-31-P (from 58.9 +- 19.7 to 56.2 +- 16.2, p = 0.035) and GAD-7 scores (from 8.8 +- 6.2 to 8.3 +- 5.9, corrected p = .024) was identified. No statistically significant longitudinal changes in the number of seizures (from 0.9 +- 1.9 to 2.5 +- 6.2, p = .125) or NDDI-E scores (from 12.3 +- 4.3 to 13.4 +- 4.4, p = .065) were found. Significant longitudinal increase of ESS (from 4.9 +- 3.7 to 7.4 +- 4.9, p = .001) was found.

Conclusions: During the COVID-19 pandemic, quality of life and anxiety levels were lower in PWE, and sleepiness levels were raised, without seizure change.

}, keywords = {Anxiety, COVID-19, Sleep, epilepsy, pandemic, quality of life}, doi = {https://doi.org/10.1111/ane.13481}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/ane.13481}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira Campos, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo-Heras, Mar{\'\i}a} } @article {907, title = {Multimodal fusion analysis of structural connectivity and gray matter morphology in migraine}, journal = {Human Brain Mapping}, volume = {42}, year = {2021}, pages = {908-921}, abstract = {

No specific migraine biomarkers have been found in single-modality MRI studies. We aimed at establishing biomarkers for episodic and chronic migraine using diverse MRI modalities. We employed canonical correlation analysis and joint independent component analysis to find structural connectivity abnormalities that are related to gray matter morphometric alterations. The number of streamlines (trajectories of estimated fiber-tracts from tractography) was employed as structural connectivity measure, while cortical curvature, thickness, surface area, and volume were used as gray matter parameters. These parameters were compared between 56 chronic and 54 episodic migraine patients, and 50 healthy controls. Cortical curvature alterations were associated with abnormalities in the streamline count in episodic migraine patients compared to controls, with higher curvature values in the frontal and temporal poles being related to a higher streamline count. Lower streamline count was found in migraine compared to controls in connections between cortical regions within each of the four lobes. Higher streamline count was found in migraine in connections between subcortical regions, the insula, and the cingulate and orbitofrontal cortex, and between the insula and the temporal region. The connections between the caudate nucleus and the orbitofrontal cortex presented worse connectivity in chronic compared to episodic migraine. The hippocampus was involved in connections with higher and lower number of streamlines in chronic migraine. Strengthening of structural networks involving pain processing and subcortical regions coexists in migraine with weakening of cortical networks within each lobe. The multimodal analysis offers a new insight about the association between brain structure and connectivity.

}, keywords = {Brain, Magnetic Resonance Imaging, connectome, diffusion magnetic resonance imaging, migraine disorders}, doi = {https://doi.org/10.1002/hbm.25267}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.25267}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Rodrigo de Luis-Garc{\'\i}a} } @article {923, title = {Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis}, journal = {Schizophrenia Research}, volume = {229}, year = {2021}, pages = {102-111}, abstract = {

Schizophrenia and bipolar disorder include patients with different characteristics, which may hamper the definition of biomarkers. One of the dimensions with greater heterogeneity among these patients is cognition. Recent studies support the identification of different patients{\textquoteright} subgroups along the cognitive domain using cluster analysis. Our aim was to validate clusters defined on the basis of patients{\textquoteright} cognitive status and to assess its relation with demographic, clinical and biological measurements. We hypothesized that subgroups characterized by different cognitive profiles would show differences in an array of biological data. Cognitive data from 198 patients (127 with chronic schizophrenia, 42 first episodes of schizophrenia and 29 bipolar patients) were analyzed by a K-means cluster approach and were compared on several clinical and biological variables. We also included 155 healthy controls for further comparisons. A two-cluster solution was selected, including a severely impaired group and a moderately impaired group. The severely impaired group was associated with higher illness duration and symptoms scores, lower thalamus and hippocampus volume, lower frontal connectivity and basal hypersynchrony in comparison to controls and the moderately impaired group. Moreover, both patients{\textquoteright} groups showed lower cortical thickness and smaller functional connectivity modulation than healthy controls. This study supports the existence of different cognitive subgroups within the psychoses with different neurobiological underpinnings.

}, keywords = {Cognition, Connectivity, Modulation, Volume, bipolar disorder, schizophrenia}, issn = {0920-9964}, doi = {https://doi.org/10.1016/j.schres.2020.11.013}, url = {https://www.sciencedirect.com/science/article/pii/S0920996420305521}, author = {Fern{\'a}ndez-Linsenbarth, In{\'e}s and {\'A}lvaro Planchuelo-G{\'o}mez and D{\'\i}ez, {\'A}lvaro and Arjona-Valladares, Antonio and Rodrigo de Luis-Garc{\'\i}a and Mart{\'\i}n-Santiago, {\'O}scar and Benito-S{\'a}nchez, Jos{\'e} Antonio and P{\'e}rez-Laureano, {\'A}ngela and Gonz{\'a}lez-Parra, David and Montes-Gonzalo, Carmen and Melero-Lerma, Raquel and Fern{\'a}ndez Morante, Sonia and Sanz-Fuentenebro, Javier and G{\'o}mez-Pilar, Javier and N{\'u}{\~n}ez-Novo, Pablo and Molina, Vicente} } @article {909, title = {Real world effectiveness and tolerability of candesartan in the treatment of migraine: a retrospective cohort study}, journal = {Scientific Reports}, volume = {11}, year = {2021}, pages = {3846}, abstract = {

To date, two randomized, controlled studies support the use of candesartan for migraine prophylaxis but with limited external validity. We aim to evaluate the effectiveness and tolerability of candesartan in clinical practice and to explore predictors of patient response. Retrospective cohort study including all patients with migraine who received candesartan between April 2008-February 2019. The primary endpoint was the number of monthly headache days during weeks 8{\textendash}12 of treatment compared to baseline. Additionally, we evaluated the frequency during weeks 20{\textendash}24. We analysed the percentage of patients with 50\% and 75\% response rates and the retention rates after three and 6\ months of treatment. 120/4121 patients were eligible, aged 45.9 [11.5]; 100 (83.3\%) female. Eighty-four patients (70\%) had chronic migraine and 53 (42.7\%) had medication-overuse headache. The median number of prior prophylactics was 3 (Inter-quartile range 2{\textendash}5). At baseline, patients had 20.5 {\textpm} 8.5 headache days per month, decreasing 4.3 {\textpm} 8.4\ days by 3\ months (weeks 12{\textendash}16) and by 4.7 {\textpm} 8.7\ days by 6\ months (paired Student{\textquoteright}s t-test, p \< 0.001). The percentage of patients with a 50\% response was 32.5\% at 3\ months and 31.7\% at 6\ months, while the retention rate was 85.0\% and 58.3\%. The number of prior treatments (Odds ratio 0.79, 95\% CI 0.64{\textendash}0.97) and the presence of daily headache (Odds ratio 0.39, 95\% CI 0.16{\textendash}0.97) were associated with a lower probability of response. Candesartan showed beneficial effects in the preventive treatment of migraine in clinical practice, including patients with chronic migraine, medication-overuse headache and resistance to prior prophylactics.

}, issn = {2045-2322}, doi = {10.1038/s41598-021-83508-2}, url = {https://doi.org/10.1038/s41598-021-83508-2}, author = {S{\'a}nchez-Rodr{\'\i}guez, Carmen and Sierra, {\'A}lvaro and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-P{\'\i}as, Enrique and {\'A}ngel L. Guerrero and Garc{\'\i}a-Azor{\'\i}n, David} } @conference {939, title = {Resting-state functional alterations in patients with persistent headache after COVID-19 infection: an exploratory study}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: To evaluate resting-state functional alterations in patients with persistent headache after COVID-19 resolution.
Methods: Exploratory case-control study. Highresolution brain resting-state functional Magnetic Resonance Imaging data were acquired in patients with
persistent headache after COVID-19 infection and healthy controls (HC). CONN toolbox (version 17) was employed to assess the resting-state functional connectivity between 84 cortical and subcortical gray matter regions of interest. Significant results were considered with p \< 0.05 (Family Discovery Rate and seed-level corrected).
Results: Ten patients with persistent headache after COVID-19 (mean age: 53.8 +- 7.8 years; nine women) and 10 HC balanced for age and sex (mean age: 51.9 +- 6.6 years; nine women) were included in the study. Statistically significant higher functional connectivity was observed in the patients with persistent headache compared to HC in 10 connections. These connections were composed of an occipital region and another region that included the isthmus cingulate gyrus, a frontal or a parietal area. In the patients, significant lower functional connectivity was found in 12 connections between the cingulate and hippocampal gyri, parietal, temporal and frontal regions.
Conclusions: Patients with persistent headache after COVID-19 infection present strengthened functional connectivity with occipital regions and weakened functional connectivity between frontal, temporal and parietal regions.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Moro, Ra{\'u}l and Rodrigo de Luis-Garc{\'\i}a} } @article {953, title = {Search for schizophrenia and bipolar biotypes using functional network properties}, journal = {Brain and Behavior}, volume = {11}, year = {2021}, pages = {e2415}, abstract = {

Introduction: Recent studies support the identification of valid subtypes within schizophrenia and bipolar disorder using cluster analysis. Our aim was to identify meaningful biotypes of psychosis based on network properties of the electroencephalogram. We hypothesized that these parameters would be more altered in a subgroup of patients also characterized by more severe deficits in other clinical, cognitive, and biological measurements.

Methods: A clustering analysis was performed using the electroencephalogram-based network parameters derived from graph-theory obtained during a P300 task of 137 schizophrenia (of them, 35 first episodes) and 46 bipolar patients. Both prestimulus and modulation of the electroencephalogram were included in the analysis. Demographic, clinical, cognitive, structural cerebral data, and the modulation of the spectral entropy of the electroencephalogram were compared between clusters. Data from 158 healthy controls were included for further comparisons.

Results: We identified two clusters of patients. One cluster presented higher prestimulus connectivity strength, clustering coefficient, path-length, and lower small-world index compared to controls. The modulation of clustering coefficient and path-length parameters was smaller in the former cluster, which also showed an altered structural connectivity network and a widespread cortical thinning. The other cluster of patients did not show significant differences with controls in the functional network properties. No significant differences were found between patients{\textasciiacute} clusters in first episodes and bipolar proportions, symptoms scores, cognitive performance, or spectral entropy modulation.

Conclusion: These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity.

}, keywords = {Biotypes, bipolar disorder, diffusion, electroencephalogram, network, schizophrenia}, doi = {https://doi.org/10.1002/brb3.2415}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/brb3.2415}, author = {Fern{\'a}ndez-Linsenbarth, In{\'e}s and {\'A}lvaro Planchuelo-G{\'o}mez and Be{\~n}o-Ruiz-de-la-Sierra, Rosa M. and D{\'\i}ez, Alvaro and Arjona, Antonio and P{\'e}rez, Adela and Rodr{\'\i}guez-Lorenzana, Alberto and del Valle, Pilar and de Luis-Garc{\'\i}a, Rodrigo and Mascialino, Guido and Holgado-Madera, Pedro and Segarra-Echevarr{\'\i}a, Rafael and Gomez-Pilar, Javier and N{\'u}{\~n}ez, Pablo and Bote-Boneaechea, Berta and Zambrana-G{\'o}mez, Antonio and Roig-Herrero, Alejandro and Molina, Vicente} } @article {924, title = {Temporal distribution of emergency room visits in patients with migraine and other headaches}, journal = {Expert Review of Neurotherapeutics}, volume = {21}, year = {2021}, pages = {599-605}, abstract = {

Background: Headache is a leading reason for presentation to the emergency department (ED) with migraine being the most frequently headache. To ensure the adequate staffing of healthcare providers during peak times of headache visits, we analyzed the temporal distribution of emergency department visits in patients presenting with headache and/or migraine.

Research design and methods: The authors conducted an ecological study, including all consecutive visits to the ED for headache. Patients were classified according to the IHS Classification. We analyzed circadian, circaseptan and circannual patterns for number of visits, comparing migraine patients with other headache patients.

Results: There were 2132 ED visits for headache, including primary headache in 1367 (64.1\%) cases; migraine in 963 (45.2\%); secondary headache in 404 (18.9\%); and unspecified headache in 366 (17.1\%). The circadian pattern showed peaks around 11:00{\textendash}13:00 and 17:00{\textendash}19:00, with visits during the night shift 45\% less frequent (p \< 0.001). The circaseptan pattern showed a peak on Monday-Tuesday and a low point on Sunday (p \< 0.007). The circannual pattern peaked in March and decreased in June.

Conclusions: ED visits for headache showed specific circadian, circaseptan and circannual variations. No differences were found in these patterns when comparing migraine patients to other headache patients.

}, doi = {10.1080/14737175.2021.1906222}, url = {https://doi.org/10.1080/14737175.2021.1906222}, author = {Garc{\'\i}a-Azor{\'\i}n, David and Abelaira-Freire, Jaime and Rodriguez-Adrada, Esther and Gonz{\'a}lez-Garc{\'\i}a, Nuria and {\'A}lvaro Planchuelo-G{\'o}mez and {\'A}ngel L. Guerrero and Porta-Etessam, Jes{\'u}s and Mart{\'\i}n-S{\'a}nchez, Francisco J} } @article {951, title = {Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy}, journal = {Scientific Reports}, volume = {11}, year = {2021}, month = {2021}, url = {https://www.nature.com/articles/s41598-021-97399-w}, author = {S. Merino-Caviedes and Guti{\'e}rrez, L. and Alfonso-Almaz{\'a}n, J. and Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Quintanilla, J. and S{\'a}nchez-Gonz{\'a}lez, J. and Marina-Breysse, M. and Gal{\'a}n-Arriola, C. and Enr{\'\i}quez-V{\'a}zquez, D. and Torres, C. and Pizarro, G. and Ib{\'a}{\~n}ez, B. and Peinado, R. and Merino, J. and P{\'e}rez-Villacast{\'\i}n, J. and Jalife. J and L{\'o}pez-Yunta, M. and V{\'a}zquez, M. and Aguado-Sierra, J. and Gonz{\'a}lez-Ferrer, J. and P{\'e}rez-Castellano, N. and Mart{\'\i}n-Fern{\'a}ndez, M. and Alberola-L{\'o}pez, C and Filgueiras-Rama, D.} } @conference {938, title = {White matter microstructural alterations in patients with persistent headache after COVID-19 infection: an exploratory study}, booktitle = {International Headache Congress 2021}, year = {2021}, month = {2021}, publisher = {International Headache Society \& European Headache Federation}, organization = {International Headache Society \& European Headache Federation}, address = {Virtual Congress}, abstract = {

Objective: To evaluate white matter alterations in patients with persistent headache after COVID-19 resolution.
Methods: Exploratory case-control study. Highresolution brain diffusion Magnetic Resonance Imaging data were acquired in patients with persistent headache after COVID-19 infection and healthy controls (HC). Tract-Based Spatial Statistics was used to compare fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD) and the return-to-axial (RTAP), return-to-origin (RTOP) and return-to-plane probability (RTPP) between the groups. RTAP, RTOP and RTPP were obtained with a new approach called AMURA (https://www.lpi.tel.uva.es/AMURA). Significant results were considered with p \< 0.05 (Family-Wise Error corrected) and region size larger than 30 mm3.
Results: Ten patients with persistent headache after COVID-19 (mean age: 53.8 +- 7.8 years; nine women) and 10 HC balanced for age and sex (mean age: 53.1 +- 7.0 years; nine women) were included in the study. Significant higher AD and lower RTPP values were found in patients with persistent headache compared to HC in five regions from the corona radiata, and the external and internal capsule. In the patients, significant lower RTPP values were identified in six additional areas from the same tracts and the superior longitudinal fasciculus. No additional changes were found.
Conclusions: White matter axonal alterations are present in patients with persistent headache after COVID-19 infection.

}, url = {https://journals.sagepub.com/doi/pdf/10.1177/03331024211034005}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Moro, Ra{\'u}l and Rodrigo de Luis-Garc{\'\i}a} } @article {946, title = {A deep learning approach for synthetic MRI based on two routine sequences and training with synthetic data}, journal = {Computer Methods and Programs in Biomedicine}, volume = {210}, year = {2021}, pages = {106371}, issn = {0169-2607}, doi = {10.1016/j.cmpb.2021.106371}, url = {https://doi.org/10.1016/j.cmpb.2021.106371}, author = {Moya-S{\'a}ez, Elisa and {\'O}scar Pe{\~n}a-Nogales and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {912, title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge}, journal = {bioRxiv}, year = {2021}, month = {2021}, doi = {10.1101/2021.03.02.433228}, url = {https://www.biorxiv.org/content/early/2021/03/02/2021.03.02.433228}, author = {De Luca, Alberto and Ianus, Andrada and Leemans, Alexander and Palombo, Marco and Shemesh, Noam and Zhang, Hui and Alexander, Daniel C and Nilsson, Markus and Froeling, Martijn and Biessels, Geert-Jan and Zucchelli, Mauro and Frigo, Matteo and Albay, Enes and Sedlar, Sara and Alimi, Abib and Deslauriers-Gauthier, Samuel and Deriche, Rachid and Fick, Rutger and Maryam Afzali and Tomasz Pieciak and Bogusz, Fabian and Santiago Aja-Fern{\'a}ndez and Ozarslan, Evren and Derek K. Jones and Chen, Haoze and Jin, Mingwu and Zhang, Zhijie and Wang, Fengxiang and Nath, Vishwesh and Parvathaneni, Prasanna and Morez, Jan and Sijbers, Jan and Jeurissen, Ben and Fadnavis, Shreyas and Endres, Stefan and Rokem, Ariel and Garyfallidis, Eleftherios and Sanchez, Irina and Prchkovska, Vesna and Rodrigues, Paulo and Landman, Bennet A and Schilling, Kurt G} } @article {933, title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge}, journal = {NeuroImage}, year = {2021}, month = {2021}, pages = {118367}, issn = {1053-8119}, doi = {https://doi.org/10.1016/j.neuroimage.2021.118367}, url = {https://www.sciencedirect.com/science/article/pii/S1053811921006431}, author = {Alberto De Luca and Andrada Ianus and Alexander Leemans and Marco Palombo and Noam Shemesh and Hui Zhang and Daniel C. Alexander and Markus Nilsson and Martijn Froeling and Geert-Jan Biessels and Mauro Zucchelli and Matteo Frigo and Enes Albay and Sara Sedlar and Abib Alimi and Samuel Deslauriers-Gauthier and Rachid Deriche and Rutger Fick and Maryam Afzali and Tomasz Pieciak and Fabian Bogusz and Santiago Aja-Fern{\'a}ndez and Evren {\"O}zarslan and Derek K. Jones and Haoze Chen and Mingwu Jin and Zhijie Zhang and Fengxiang Wang and Vishwesh Nath and Prasanna Parvathaneni and Jan Morez and Jan Sijbers and Ben Jeurissen and Shreyas Fadnavis and Stefan Endres and Ariel Rokem and Eleftherios Garyfallidis and Irina Sanchez and Vesna Prchkovska and Paulo Rodrigues and Bennet A. Landman and Kurt G. Schilling} } @conference {917, title = {The utility of the GAD-7 anxiety, NDDI-E depression, Epworth sleepiness and QOLIE-31-P quality of life scales in patients with epilepsy in real clinical practice (2379)}, booktitle = {Proceedings of the American Academy of Neurology 2021 Virtual Annual Meeting}, year = {2021}, publisher = {Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology}, organization = {Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology}, abstract = {

Objective: The objective of this project is to study the presence of psychiatric comorbidity (anxiety and depression), somnolence and quality of life using validated scales in patients with epilepsy in real clinical practice, and its relationship with other clinical and demographic variables.

Background: Previous studies have shown that psychiatric comorbidity, specially anxiety and depression, as well as sleep disorders are more prevalent in patients with epilepsy than in the general population.

Design/Methods: Cross-sectional descriptive observational study using validated scales of anxiety disorders(GAD-7), depression(NDDI-E), sleep disorders(Epworth) and quality of life(QOLIE-31-P) in patients with epilepsy treated in the Refractory Epilepsy Unit of a tertiary hospital.

Results: We recruited 84 patients, age 44.3 {\textpm} 17.4 years, 48.2\% women, duration of epilepsy 21.5 {\textpm} 15.9 years, number of antiepileptic drugs 1.9 {\textpm} 1.2. We found severe anxiety(GAD-7\> 14) in 14.3\%, depression(NDDI-E\> 15) in 20.2\%; abnormal sleepiness(Epworth\> 10) in 14.3\% of patients, and QOLIE-31-P 62.0 {\textpm} 19.2. Each more point in GAD-7 is 21\% more likely to suffer from anxiety(OR 1.21; 95\% CI 1.09{\textendash}1.36; p = 0.0008), NDDI-E scores\<=15 represent 85 \% less chance of having depression(OR 0.15; 95\% CI 0.04{\textendash}0.51]; p = 0.002). We found a positive association between depression according to NDDI-E with seizure frequency(p = 0.017) and number of drugs(p = 0.019); and severe anxiety according to GAD-7 and number of drugs(p = 0.019). We found a negative correlation between QOLIE-31-P with NDDI-E(r = -0.68; p \<0.0001) and GAD-7(r = -0.76; p \<0.0001).

Conclusions: Validated scales in epilepsy for the detection of anxiety(GAD-7) and depression(NDDI-E) are useful in the detection of these disorders in real clinical practice. The assessment of the presence of anxiety-depressive psychiatric comorbidity is especially relevant in patients with a higher frequency of seizures, a greater number of drugs and a poorer quality of life.

}, url = {https://n.neurology.org/content/96/15_Supplement/2379}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-Dubarbie, Francisco and Vieira Campos, Alba and Vivancos, Jos{\'e} and De Toledo, Mar{\'\i}a} } @proceedings {856, title = {AMURA with standard single-shell acquisition can detect changes beyond the Diffusion Tensor: a migraine clinical study}, volume = {4549}, year = {2020}, month = {2020}, abstract = {AMURA (Apparent Measures Using Reduced Acquisitions) is an alternative formulation to drastically reduce the number of samples needed for the estimation of diffusion properties related to the Ensemble Average diffusion Propagator (EAP). Although these measures were initially intended for medium-to-high b-values, in this work we evaluate their performance in DTI-like acquisitions. Fifty healthy controls, 54 episodic migraine (EM) and 56 chronic migraine (CM) patients were compared, using a single-shell diffusion scheme at b=1000 s/mm2. We compare AMURA measures (return-to-origin, return-to-axis and return-to-plane probabilities) to traditional DTI measures. Differences between EM and controls were only detectable using the return-to-origin probability.}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez} } @inbook {895, title = {Alternative Diffusion Anisotropy Metric from Reduced MRI Acquisitions}, booktitle = {Computational Diffusion MRI}, year = {2020}, pages = {13{\textendash}24}, publisher = {Springer, Cham}, organization = {Springer, Cham}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Rodrigo de Luis-Garc{\'\i}a and Derek K. Jones} } @article {891, title = {Alternative Microstructural Measures to Complement Diffusion Tensor Imaging in Migraine Studies with Standard MRI Acquisition}, journal = {Brain Sciences}, volume = {10}, year = {2020}, month = {2020}, pages = {711}, abstract = {The white matter state in migraine has been investigated using diffusion tensor imaging (DTI) measures, but results using this technique are conflicting. To overcome DTI measures, we employed ensemble average diffusion propagator measures obtained with apparent measures using reduced acquisitions (AMURA). The AMURA measures were return-to-axis (RTAP), return-to-origin (RTOP) and return-to-plane probabilities (RTPP). Tract-based spatial statistics was used to compare fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity from DTI, and RTAP, RTOP and RTPP, between healthy controls, episodic migraine and chronic migraine patients. Fifty healthy controls, 54 patients with episodic migraine and 56 with chronic migraine were assessed. Significant differences were found between both types of migraine, with lower axial diffusivity values in 38 white matter regions and higher RTOP values in the middle cerebellar peduncle in patients with a chronic migraine (p \< 0.05 family-wise error corrected). Significantly lower RTPP values were found in episodic migraine patients compared to healthy controls in 24 white matter regions (p \< 0.05 family-wise error corrected), finding no significant differences using DTI measures. The white matter microstructure is altered in a migraine, and in chronic compared to episodic migraine. AMURA can provide additional results with respect to DTI to uncover white matter alterations in migraine.}, issn = {2076-3425}, doi = {10.3390/brainsci10100711}, url = {https://www.mdpi.com/2076-3425/10/10/711}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Rodrigo de Luis-Garc{\'\i}a and Rodr{\'\i}guez, Margarita and Santiago Aja-Fern{\'a}ndez} } @article {868, title = {Automatic non-destructive video estimation of maturation levels in Fuji apple (Malus Malus pumila) fruit in orchard based on colour (Vis) and spectral (NIR) data}, journal = {Biosystems Engineering}, volume = {195}, year = {2020}, pages = {136{\textendash}151}, abstract = {Non-destructive estimates information on the desired properties of fruit without damaging them. The objective of this work is to present an algorithm for the automatic and non-destructive estimation of four maturity stages (unripe, half-ripe, ripe, or overripe) of Fuji apples (Malus Malus pumila) using both colour and spectral data from fruit. In order to extract spectral and colour data to train a proposed system, 170 samples of Fuji apples were collected. Colour and spectral features were extracted using a CR-400 Chroma Meter colorimeter and a custom set up. The second component of colour space and near infrared (NIR) spectrum data in wavelength ranges of 535{\textendash}560 nm, 835{\textendash}855 nm, and 950{\textendash}975 nm, were used to train the proposed algorithm. A hybrid artificial neural network-simulated annealing algorithm (ANN-SA) was used for classification purposes. A total of 1000 iterations were conducted to evaluate the reliability of the classification process. Results demonstrated that after training the correction classification rate (CCR, accuracy) was, at the best state, 100\% (test set) using both colour and spectral data. The CCR of the four different classifiers were 93.27\%, 99.62\%, 98.55\%, and 99.59\%, for colour features, spectral data wavelength ranges of 535{\textendash}560 nm, 835{\textendash}855 nm, and 950{\textendash}975 nm, respectively, over the test set. These results suggest that the proposed method is capable of the non-destructive estimation of different maturity stages of Fuji apple with a remarkable accuracy, in particular within the 535{\textendash}560 nm wavelength range.}, doi = {https://doi.org/10.1016/j.biosystemseng.2020.04.015}, url = {https://www.sciencedirect.com/science/article/pii/S1537511020301148}, author = {Pourdarbani, Razieh and Sabzi, Sajad and Kalantari, Davood and Karimzadeh, Rouhollah and Ilbeygi, Elham and J I Arribas} } @article {864, title = {A Computer Vision System Based on Majority-Voting Ensemble Neural Network for the Automatic Classification of Three Chickpea Varieties}, journal = {Foods}, volume = {9}, year = {2020}, pages = {113}, abstract = {Since different varieties of crops have specific applications, it is therefore important to properly identify each cultivar, in order to avoid fake varieties being sold as genuine, i.e., fraud. Despite that properly trained human experts might accurately identify and classify crop varieties, computer vision systems are needed since conditions such as fatigue, reproducibility, and so on, can influence the expert{\textquoteright}s judgment and assessment. Chickpea (Cicer arietinum L.) is an important legume at the world-level and has several varieties. Three chickpea varieties with a rather similar visual appearance were studied here: Adel, Arman, and Azad chickpeas. The purpose of this paper is to present a computer vision system for the automatic classification of those chickpea varieties. First, segmentation was performed using an Hue Saturation Intensity (HSI) color space threshold. Next, color and textural (from the gray level co-occurrence matrix, GLCM) properties (features) were extracted from the chickpea sample images. Then, using the hybrid artificial neural network-cultural algorithm (ANN-CA), the sub-optimal combination of the five most effective properties (mean of the RGB color space components, mean of the HSI color space components, entropy of GLCM matrix at 90{\textdegree}, standard deviation of GLCM matrix at 0{\textdegree}, and mean third component in YCbCr color space) were selected as discriminant features. Finally, an ANN-PSO/ACO/HS majority voting (MV) ensemble methodology merging three different classifier outputs, namely the hybrid artificial neural network-particle swarm optimization (ANN-PSO), hybrid artificial neural network-ant colony optimization (ANN-ACO), and hybrid artificial neural network-harmonic search (ANN-HS), was used. Results showed that the ensemble ANN-PSO/ACO/HS-MV classifier approach reached an average classification accuracy of 99.10 {\textpm} 0.75\% over the test set, after averaging 1000 random iterations.}, doi = {https://doi.org/10.3390/foods9020113}, url = {https://www.mdpi.com/2304-8158/9/2/113}, author = {Pourdarbani, Razieh and Sabzi, Sajad and Kalantari, Davood and Hern{\'a}ndez-Hern{\'a}ndez, Jos{\'e} Luis and J I Arribas} } @article {865, title = {A Computer Vision System for the Automatic Classification of Five Varieties of Tree Leaf Images}, journal = {Computers}, volume = {9}, year = {2020}, pages = {6}, abstract = {A computer vision system for automatic recognition and classification of five varieties of plant leaves under controlled laboratory imaging conditions, comprising: 1{\textendash}Cydonia oblonga (quince), 2{\textendash}Eucalyptus camaldulensis dehn (river red gum), 3{\textendash}Malus pumila (apple), 4{\textendash}Pistacia atlantica (mt. Atlas mastic tree) and 5{\textendash}Prunus armeniaca (apricot), is proposed. 516 tree leaves images were taken and 285 features computed from each object including shape features, color features, texture features based on the gray level co-occurrence matrix, texture descriptors based on histogram and moment invariants. Seven discriminant features were selected and input for classification purposes using three classifiers: hybrid artificial neural network{\textendash}ant bee colony (ANN{\textendash}ABC), hybrid artificial neural network{\textendash}biogeography based optimization (ANN{\textendash}BBO) and Fisher linear discriminant analysis (LDA). Mean correct classification rates (CCR), resulted in 94.04\%, 89.23\%, and 93.99\%, for hybrid ANN{\textendash}ABC; hybrid ANN{\textendash}BBO; and LDA classifiers, respectively. Best classifier mean area under curve (AUC), mean sensitivity, and mean specificity, were computed for the five tree varieties under study, resulting in: 1{\textendash}Cydonia oblonga (quince) 0.991 (ANN{\textendash}ABC), 95.89\% (ANN{\textendash}ABC), 95.91\% (ANN{\textendash}ABC); 2{\textendash}Eucalyptus camaldulensis dehn (river red gum) 1.00 (LDA), 100\% (LDA), 100\% (LDA); 3{\textendash}Malus pumila (apple) 0.996 (LDA), 96.63\% (LDA), 94.99\% (LDA); 4{\textendash}Pistacia atlantica (mt. Atlas mastic tree) 0.979 (LDA), 91.71\% (LDA), 82.57\% (LDA); and 5{\textendash}Prunus armeniaca (apricot) 0.994 (LDA), 88.67\% (LDA), 94.65\% (LDA), respectively.}, doi = {https://doi.org/10.3390/computers9010006}, url = {https://www.mdpi.com/2073-431X/9/1/6}, author = {Sabzi, Sajad and Pourdarbani, Razieh and J I Arribas} } @article {904, title = {Deep Phenotyping of Headache in Hospitalized COVID-19 Patients via Principal Component Analysis}, journal = {Frontiers in Neurology}, volume = {11}, year = {2020}, pages = {1751}, abstract = {

Objectives: Headache is a common symptom in systemic infections, and one of the symptoms of the novel coronavirus disease 2019 (COVID-19). The objective of this study was to characterize the phenotype of COVID-19 headache via machine learning.Methods: We performed a cross-sectional study nested in a retrospective cohort. Hospitalized patients with COVID-19 confirmed diagnosis who described headache were included in the study. Generalized Linear Models and Principal Component Analysis were employed to detect associations between intensity and self-reported disability caused by headache, quality and topography of headache, migraine features, COVID-19 symptoms, and results from laboratory tests.Results: One hundred and six patients were included in the study, with a mean age of 56.6 {\textpm} 11.2, including 68 (64.2\%) females. Higher intensity and/or disability caused by headache were associated with female sex, fever, abnormal platelet count and leukocytosis, as well as migraine symptoms such as aggravation by physical activity, pulsating pain, and simultaneous photophobia and phonophobia. Pain in the frontal area (83.0\% of the sample), pulsating quality, higher intensity of pain, and presence of nausea were related to lymphopenia. Pressing pain and lack of aggravation by routine physical activity were linked to low C-reactive protein and procalcitonin levels.Conclusion: Intensity and disability caused by headache attributed to COVID-19 are associated with the disease state and symptoms. Two distinct headache phenotypes were observed in relation with COVID-19 status. One phenotype seems to associate migraine symptoms with hematologic and inflammatory biomarkers of severe COVID-19; while another phenotype would link tension-type headache symptoms to milder COVID-19.

}, issn = {1664-2295}, doi = {10.3389/fneur.2020.583870}, url = {https://www.frontiersin.org/article/10.3389/fneur.2020.583870}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Trigo, Javier and Rodrigo de Luis-Garc{\'\i}a and {\'A}ngel L. Guerrero and Porta-Etessam, Jes{\'u}s and Garc{\'\i}a-Azor{\'\i}n, David} } @article {839, title = {Direction-averaged diffusion-weighted MRI signal using different axisymmetric B-tensor encoding schemes}, journal = {Magnetic Resonance in Medicine}, volume = {n/a}, year = {2020}, month = {2020}, keywords = {B-tensor encoding, diffusion-weighted~MRI, direction-averaged diffusion signal, high b-value, power-law}, doi = {10.1002/mrm.28191}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28191}, author = {Maryam Afzali and Santiago Aja-Fern{\'a}ndez and Derek K. Jones} } @article {zhao2020doa, title = {DoA Prediction Based Beamforming with Low Training Overhead for Highly-Mobile UAV Communication with Cellular Networks}, journal = {Applied Sciences}, volume = {10}, number = {13}, year = {2020}, pages = {4420}, publisher = {Multidisciplinary Digital Publishing Institute}, author = {Zhao, Tianxiao and Luo, Chunbo and Zhou, Jianming and Guo, Dechun and Chen, Ning and Pablo Casaseca-de-la-Higuera} } @article {887, title = {Factors associated with the presence of headache in hospitalized COVID-19 patients and impact on prognosis: a retrospective cohort study}, journal = {The Journal of Headache and Pain}, volume = {21}, year = {2020}, month = {Jul}, pages = {94}, abstract = {Headache is one of the most frequent neurologic manifestations in COVID-19. We aimed to analyze which symptoms and laboratory abnormalities were associated with the presence of headache and to evaluate if patients with headache had a higher adjusted in-hospital risk of mortality.}, issn = {1129-2377}, doi = {10.1186/s10194-020-01165-8}, url = {https://doi.org/10.1186/s10194-020-01165-8}, author = {Trigo, Javier and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-P{\'\i}as, Enrique and Talavera, Blanca and Hern{\'a}ndez-P{\'e}rez, Isabel and Valle-Pe{\~n}acoba, Gonzalo and Sim{\'o}n-Campo, Paula and de Lera, Mercedes and Chavarr{\'\i}a-Miranda, Alba and L{\'o}pez-Sanz, Cristina and Guti{\'e}rrez-S{\'a}nchez, Mar{\'\i}a and Mart{\'\i}nez-Velasco, Elena and Pedraza, Mar{\'\i}a and Sierra, {\'A}lvaro and G{\'o}mez-Vicente, Beatriz and Juan F Arenillas and {\'A}ngel L. Guerrero} } @proceedings {857, title = {Fewer number of gradient directions in diffusion MRI can be counterbalanced with higher sample size: a migraine clinical study}, volume = {4550}, year = {2020}, month = {2020}, abstract = {The effect of changes in the acquisition parameters on Diffusion Tensor Imaging (DTI) has been studied, but for very specific situations. A whole-brain comparison of 54 episodic migraine (EM) and 56 chronic migraine (CM) patients, using diffusion schemes of 61, 40 and 21 gradient orientations, was performed. Statistical comparisons were repeated reducing the sample size until no significant differences were found. Higher number of regions with significant lower axial diffusivity in CM compared to EM were found using 61 gradient directions. With a larger sample size, results with 40 and 21 directions were equivalent to results acquired with 61 directions.}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Santiago Aja-Fern{\'a}ndez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Rodrigo de Luis-Garc{\'\i}a} } @article {892, title = {Gray Matter Structural Alterations in Chronic and Episodic Migraine: A Morphometric Magnetic Resonance Imaging Study}, journal = {Pain Medicine}, volume = {21}, year = {2020}, pages = {2997-3011}, abstract = {

This study evaluates different parameters describing the gray matter structure to analyze differences between healthy controls, patients with episodic migraine, and patients with chronic migraine.Cohort study.Spanish community.Fifty-two healthy controls, 57 episodic migraine patients, and 57 chronic migraine patients were included in the study and underwent T1-weighted magnetic resonance imaging acquisition.Eighty-four cortical and subcortical gray matter regions were extracted, and gray matter volume, cortical curvature, thickness, and surface area values were computed (where applicable). Correlation analysis between clinical features and structural parameters was performed.Statistically significant differences were found between all three groups, generally consisting of increases in cortical curvature and decreases in gray matter volume, cortical thickness, and surface area in migraineurs with respect to healthy controls. Furthermore, differences were also found between chronic and episodic migraine. Significant correlations were found between duration of migraine history and several structural parameters.Migraine is associated with structural alterations in widespread gray matter regions of the brain. Moreover, the results suggest that the pattern of differences between healthy controls and episodic migraine patients is qualitatively different from that occurring between episodic and chronic migraine patients.

}, issn = {1526-2375}, doi = {10.1093/pm/pnaa271}, url = {https://doi.org/10.1093/pm/pnaa271}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Rodr{\'\i}guez, Margarita and Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a} } @article {853, title = {Groupwise Non-Rigid Registration with Deep Learning: An Affordable Solution Applied to 2D Cardiac Cine MRI Reconstruction}, journal = {Entropy}, volume = {22}, year = {2020}, pages = {687}, doi = {https://doi.org/10.3390/e22060687}, url = {https://www.mdpi.com/1099-4300/22/6/687}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Sevilla, Teresa and Revilla-Orodea, Ana and Pablo Casaseca-de-la-Higuera and Alberola-L{\'o}pez, Carlos} } @article {843, title = {Identificacion of MRI-based psychosis subtypes: Replication and refinement}, journal = {Progress in Neuro-Psychopharmacology and Biological Psychiatry}, volume = {100}, year = {2020}, pages = {109907}, abstract = {

The identification of the cerebral substrates of psychoses such as schizophrenia and bipolar disorder is likely hampered by its biological heterogeneity, which may contribute to the low replication of results in the field. In this study we aimed to replicate in a completely new sample and supplement the results of a previous study with additional data on this topic. In the aforementioned study we identified a schizophrenia cluster characterized by high mean cortical curvature and low cortical thickness, subcortical hypometabolism and progressive negative symptoms. Here, we have used magnetic resonance images from 61 schizophrenia and 28 bipolar patients, as well as 51 healthy controls and a cluster analysis to search for possible subgroups primarily characterized by cerebral structural data. Diffusion tensor imaging (fractional anisotropy, FA), cognition, clinical data and electroencephalographic (EEG) modulation during a P300 task were used to validate the possible clusters. Two clusters of patients were identified. The first cluster (29 schizophrenia and 18 bipolar patients) showed decreased cortical thickness and area values, as well as lower subcortical volumes and higher cortical curvature in some regions, as compared to the second cluster. This first cluster also showed decreased FA in frontal lobe connections and worse cognitive performance. Although this cluster also showed longer illness duration, there were first episode patients in both clusters and treatment doses and types were not different between clusters. Both clusters of patients showed decreased EEG task-related modulation. In conclusion, our data give additional support to a distinct biologically based cluster encompassing schizophrenia and bipolar disorder patients with cortical and subcortical alterations, hampered cortical connectivity and lower cognitive performance.

}, keywords = {Biotypes, Cortical thickness, Curvature, Subtypes, bipolar disorder, schizophrenia}, issn = {0278-5846}, doi = {https://doi.org/10.1016/j.pnpbp.2020.109907}, url = {http://www.sciencedirect.com/science/article/pii/S0278584619309595}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Lubeiro, Alba and N{\'u}{\~n}ez-Novo, Pablo and Gomez-Pilar, Javier and Rodrigo de Luis-Garc{\'\i}a and del Valle, Pilar and Mart{\'\i}n-Santiago, {\'O}scar and P{\'e}rez-Escudero, Adela and Vicente Molina} } @article {854, title = {Integration of an Intelligent Tutoring System in a Magnetic Resonance Simulator for Education: Technical Feasibility and User Experience}, journal = {Computer Methods and Programs in Biomedicine}, year = {2020}, pages = {105634}, doi = {https://doi.org/10.1016/j.cmpb.2020.105634}, url = {https://authors.elsevier.com/a/1bM7z_3sJeWiZh}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Bote-Lorenzo, Miguel L and G{\'o}mez-S{\'a}nchez, Eduardo and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {890, title = {Longitudinal evaluation of the psychological impact of the COVID-19 crisis in Spain}, journal = {Journal of Affective Disorders}, volume = {277}, year = {2020}, pages = {842-849}, abstract = {Background: Strict confinement and social distancing measures have been imposed due to the COVID-19 pandemic in many countries. The aim was to assess the temporal evolution of the psychological impact of the COVID-19 crisis and lockdown from two surveys, separated by one month, performed in Spain. Methods: Symptoms of depression, anxiety and stress, and the psychological impact of the situation were longitudinally analyzed using the Depression Anxiety and Stress Scale (DASS-21) and the Impact of Event Scale (IES) respectively. Results: There was a total of 4,724 responses from both surveys. Symptomatic scores of anxiety, depression and stress were exhibited by 37.22\%, 46.42\% and 49.66\% of the second survey respondents, showing a significant increase compared to the first survey (32.45\%, 44.11\% and 37.01\%, respectively). There was no significant longitudinal change of the IES scores, with 48.30\% of the second survey participants showing moderate to severe impact of the confinement. Constant news consumption about COVID-19 was found to be positively associated with symptomatic scores in the different scales, and daily physical activity to be negatively associated with DASS-21 scores. Conclusions: Results indicated a temporal increase of anxiety, depression and stress scores during the COVID-19 lockdown. Factors such as age, consumption of information about COVID-19 and physical activity seem to have an important impact on the evolution of psychological symptoms.}, keywords = {Anxiety, COVID-19, Depression, Longitudinal study, Post-traumatic, Psychological, Stress, Stress disorders}, issn = {0165-0327}, doi = {10.1016/j.jad.2020.09.018}, url = {http://www.sciencedirect.com/science/article/pii/S0165032720327130}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Odriozola-Gonz{\'a}lez, Paula and Irurtia, Mar{\'\i}a Jes{\'u}s and Rodrigo de Luis-Garc{\'\i}a} } @article {844, title = {Micro-structure diffusion scalar measures from reduced MRI acquisitions}, journal = {PLOS ONE}, volume = {15}, year = {2020}, month = {2020}, pages = {1-25}, abstract = {

In diffusion MRI, the Ensemble Average diffusion Propagator (EAP) provides relevant micro-structural information and meaningful descriptive maps of the white matter previously obscured by traditional techniques like Diffusion Tensor Imaging (DTI). The direct estimation of the EAP, however, requires a dense sampling of the Cartesian q-space involving a huge amount of samples (diffusion gradients) for proper reconstruction. A collection of more efficient techniques have been proposed in the last decade based on parametric representations of the EAP, but they still imply acquiring a large number of diffusion gradients with different b-values (shells). Paradoxically, this has come together with an effort to find scalar measures gathering all the q-space micro-structural information probed in one single index or set of indices. Among them, the return-to-origin (RTOP), return-to-plane (RTPP), and return-to-axis (RTAP) probabilities have rapidly gained popularity. In this work, we propose the so-called {\textquotedblleft}Apparent Measures Using Reduced Acquisitions{\textquotedblright} (AMURA) aimed at computing scalar indices that can mimic the sensitivity of state of the art EAP-based measures to micro-structural changes. AMURA drastically reduces both the number of samples needed and the computational complexity of the estimation of diffusion properties by assuming the diffusion anisotropy is roughly independent from the radial direction. This simplification allows us to compute closed-form expressions from single-shell information, so that AMURA remains compatible with standard acquisition protocols commonly used even in clinical practice. Additionally, the analytical form of AMURA-based measures, as opposed to the iterative, non-linear reconstruction ubiquitous to full EAP techniques, turns the newly introduced apparent RTOP, RTPP, and RTAP both robust and efficient to compute.

}, doi = {10.1371/journal.pone.0229526}, url = {https://doi.org/10.1371/journal.pone.0229526}, author = {Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a and Maryam Afzali and Molendowska, Malwina and Tomasz Pieciak and Antonio Trist{\'a}n-Vega} } @article {869, title = {Non-destructive Estimation of Chlorophyll a Content in Red Delicious Apple Cultivar Based on Spectral and Color Data}, journal = {Journal of Agricultural Sciences}, volume = {26}, year = {2020}, pages = {339{\textendash}348}, abstract = {Non-destructive estimation of the chemical properties of fruit is an important goal of researchers in the food industry, since online operations, such as fruit packaging based on the amount of different chemical properties and determining different stages of handling, are done based on these estimations. In this study, chlorophyll a content in Red Delicious apple cultivar is predicted as a chemical property that is altered by apple ripening stage, using non-destructive spectral and color methods combined. Two artificial intelligence methods based on hybrid Multilayer Perceptron Neural Network - Artificial Bee Colony Algorithm (ANN-ABC) and Partial least squares regression (PLSR) were used in order to obtain a non-destructive estimation of chlorophyll a content. In application of the PLSR method, various pre-processing algorithms were used. In order to statistically properly validate the hybrid ANN-ABC predictive method, 20 runs were performed. Results showed that the best regression coefficient of the PLSR method in predicting chlorophyll a content using spectral data alone was 0.918. At the same time, the average determination coefficient over 20 repetitions in hybrid ANN-ABC in the estimation of chlorophyll a content, using spectral data and color features were higher than 0.92{\textpm}0.040 and 0.89{\textpm}0.045, respectively, which to our knowledge is a remarkable non-intrusive estimation result.}, doi = {https://doi.org/10.15832/ankutbd.523574}, url = {https://dergipark.org.tr/en/pub/ankutbd/issue/56429/523574}, author = {Yousef Abbaspour-Gilandeh and Sabzi, Sajad and Azadshahraki, Farzad and Karimzadeh, Rouhollah and Ilbeygi, Elham and J I Arribas} } @article {870, title = {Non-destructive visible and short-wave near-infrared spectroscopic data estimation of various physicochemical properties of Fuji apple (Malus pumila) fruits at different maturation stages}, journal = {Chemometrics and Intelligent Laboratory Systems}, year = {2020}, pages = {104147}, abstract = {measurement of physicochemical properties of fruits during maturation stages can help having proper fruit management. Spectroscopy data analyzing and processing is among the commonly used methods that enable non-destructive accurate property estimation. Non-destructive linear (partial least squares regression, PSLR) and non-linear (artificial neural network, ANN) regression estimation of different physicochemical properties including firmness, acidity (pH) and starch content of 160 Fuji (Malus pumila) apple fruit samples at various maturity stages using visible and short wave near infrared (VSWIR) spectroscopic data in wavelength range 400{\textendash}1000 nm is investigated with the following steps: (1) harvesting 160 Fuji apple samples at four different maturation levels; (2) extracting spectral data in wavelength range of 400{\textendash}1000 nm; extracting physicochemical properties of tissue firmness, acidity (pH) and starch content; (3) pre-processing the reflectance spectra from each sample; (4) selecting effective wavelength values for each chemical property; and (5) non-destructive estimation of tissue firmness, acidity (pH) and starch content using spectral data range 400{\textendash}1000 nm and spectral data based on effective wavelengths, by means of an ensemble average artificial neural network method. Results show that the neural ensemble reached similar results when using VSWIR spectral data content (wavelength range) and fixed effective selected NIR wavelengths. Correlation coefficients estimating tissue firmness, acidity (pH), and starch content were 0.800, 0.919, and 0.940 for VSWIR spectral data (linear PLS regression), 0.826, 0.947, and 0.969 for VSWIR spectral data (non-linear ANN), 0.827, 0.946, and 0.969 for fixed NIR effective wavelengths (non-linear ANN). Mean {\textpm} std. Regression coefficients for tissue firmness, acidity (pH), and starch content were 0.717 {\textpm} 0.113, 0.786 {\textpm} 0.131, and 0.941 {\textpm} 0.013 for Vis/NIR spectral data (linear PLS regression), 0.849 {\textpm} 0.017, 0.930 {\textpm} 0.017, and 0.967 {\textpm} 0.007 for Vis/NIR spectral data (non-linear ANN), 0.852 {\textpm} 0.016, 0.929 {\textpm} 0.015, and 0.966 {\textpm} 0.006 for fixed effective NIR wavelengths (non-linear ANN).}, doi = {https://doi.org/10.1016/j.chemolab.2020.104147}, url = {https://www.sciencedirect.com/science/article/pii/S016974392030304X}, author = {Pourdarbani, Razieh and Sabzi, Sajad and Kalantari, Davood and J I Arribas} } @article {842, title = {Objective ADHD diagnosis using Convolutional Neural Networks over Daily-Life Activity Records}, journal = {IEEE Journal of Biomedical and Health Informatics}, year = {2020}, author = {Amado-Caballero, Patricia and Pablo Casaseca-de-la-Higuera and Alberola-Lopez, Susana and Jesus Maria Andres-de-Llano and Lopez-Villalobos, Jose Antonio and Garmendia-Leiza, Jose Ramon and Carlos Alberola-Lopez} } @article {888, title = {Phenotypic characterization of acute headache attributed to SARS-CoV-2: An ICHD-3 validation study on 106 hospitalized patients}, journal = {Cephalalgia}, volume = {40}, year = {2020}, month = {2020}, pages = {1432-1442}, abstract = {Introduction: Headache is a common symptom of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In this study, we aimed to characterize the phenotype of headache attributed to SARS-CoV-2 infection and to test the International Classification of Headache Disorders (ICHD-3) phenotypic criteria for migraine and tension-type headache. Methods: The study design was a cross-sectional study nested in a cohort. We screened all consecutive patients that were hospitalized and had a positive SARS-CoV-2 test. We included patients that described headache if the headache was not better explained by another ICHD-3 diagnosis. Patients were interviewed by two neurologists. Results: We screened 580 patients and included 130 (mean age 56 years, 64\% female). Headache was the first symptom of the infection in 26\% of patients and appeared within 24 hours in 62\% of patients. The headache was bilateral in 85\%, frontal in 83\%, and with pressing quality in 75\% of patients. Mean intensity was 7.1, being severe in 64\%. Hypersensitivity to stimuli occurred in 57\% of patients. ICHD-3 criteria for headache attributed to systemic viral infection were fulfilled by 94\% of patients; phenotypic criteria for migraine were fulfilled by 25\% of patients, and tension-type headache criteria by 54\% of patients. Conclusion: Headache attributed to SARS-CoV-2 infection in hospitalized patients has severe intensity, frontal predominance and oppressive quality. It occurs early in the course of the disease. Most patients fulfilled ICHD-3 criteria for headache attributed to systemic viral infection; however, the phenotype might resemble migraine in a quarter of cases and tension-type headache in half of the patients.}, issn = {0333-1024}, doi = {10.1177/0333102420965146}, url = {https://doi.org/10.1177/0333102420965146}, author = {Trigo L{\'o}pez, Javier and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Iglesias, Cristina and Due{\~n}as-Guti{\'e}rrez, Carlos and {\'A}ngel L. Guerrero} } @article {850, title = {Psychological effects of the COVID-19 outbreak and lockdown among students and workers of a Spanish university}, journal = {Psychiatry Research}, volume = {290}, year = {2020}, pages = {113108}, abstract = {The aim of this study was to analyze the psychological impact of COVID-19 in the university community during the first weeks of confinement. A cross-sectional study was conducted. The Depression Anxiety Stress Scale (DASS-21) was employed to assess symptoms of depression, anxiety and stress. The emotional impact of the situation was analyzed using the Impact of Event Scale. An online survey was fulfilled by 2530 members of the University of Valladolid, in Spain. Moderate to extremely severe scores of anxiety, depression, and stress were reported by 21.34\%, 34.19\% and 28.14\% of the respondents, respectively. A total of 50.43\% of respondents presented moderate to severe impact of the outbreak. Students from Arts \& Humanities and Social Sciences \& Law showed higher scores related to anxiety, depression, stress and impact of event with respect to students from Engineering \& Architecture. University staff presented lower scores in all measures compared to students, who seem to have suffered an important psychological impact during the first weeks of the COVID-19 lockdown. In order to provide timely crisis-oriented psychological services and to take preventive measures in future pandemic situations, mental health in university students should be carefully monitored.}, keywords = {Anxiety, Depression, Psychological impact, Stress, University students}, issn = {0165-1781}, doi = {https://doi.org/10.1016/j.psychres.2020.113108}, url = {http://www.sciencedirect.com/science/article/pii/S0165178120313147}, author = {Odriozola-Gonz{\'a}lez, Paula and {\'A}lvaro Planchuelo-G{\'o}mez and Irurtia, Mar{\'\i}a Jes{\'u}s and Rodrigo de Luis-Garc{\'\i}a} } @article {889, title = {Psychological symptoms of the outbreak of the COVID-19 confinement in Spain}, journal = {Journal of Health Psychology}, year = {2020}, pages = {1359105320967086}, abstract = {We studied the short-term psychological effects of the COVID-19 crisis and the quarantine on 3550 adults from the Spanish population in a cross-sectional survey. Symptoms of anxiety, depression, and stress were analyzed using the 21-item version of the Depression Anxiety Stress Scale. Symptoms of posttraumatic stress disorder were analyzed using the Impact of Event Scale. Symptomatic scores of anxiety, depression, and stress were observed in 20\% to 30\% of respondents. Symptomatic scores indicating psychological stress were found in 47.5\% of respondents. Similar to the findings of other multiple studies, confinement has been found to have significant emotional impact in the Spanish population.}, issn = {1359-1053}, doi = {10.1177/1359105320967086}, url = {https://doi.org/10.1177/1359105320967086}, author = {Odriozola-Gonz{\'a}lez, Paula and {\'A}lvaro Planchuelo-G{\'o}mez and Irurtia, Mar{\'\i}a Jes{\'u}s and Rodrigo de Luis-Garc{\'\i}a} } @article {914, title = {Q-space quantitative diffusion MRI measures using a stretched-exponential representation}, journal = {arXiv}, year = {2020}, url = {https://arxiv.org/abs/2009.07376}, author = {Tomasz Pieciak and Maryam Afzali and Fabian Bogusz and Santiago Aja-Fern{\'a}ndez and Derek K. Jones} } @article {903, title = {Response prediction for chronic migraine preventive treatment by gray matter morphometry in magnetic resonance imaging: a pilot study}, journal = {Revista de Neurologia}, volume = {71}, year = {2020}, pages = {399-406}, doi = {10.33588/rn.7111.2020488}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Ant{\'o}n-Juarros, Saray and Rodrigo de Luis-Garc{\'\i}a} } @article {897, title = {Simultaneous imaging of hard and soft biological tissues in a low-field dental MRI scanner}, journal = {Scientific Reports volume }, volume = {10}, year = {2020}, month = {2020}, chapter = {21470}, doi = {https://doi.org/10.1038/s41598-020-78456-2}, url = {https://www.nature.com/articles/s41598-020-78456-2}, author = {Jos{\'e} M. Algar{\'\i}n and Elena D{\'\i}az-Caballero and Jos{\'e} Borreguero and Fernando Galve and Daniel Grau-Ruiz and Juan P. Rigla and Rub{\'e}n Bosch and Jos{\'e} M. Gonz{\'a}lez and Eduardo Pall{\'a}s and Miguel Corber{\'a}n and Carlos Gramage and Santiago Aja-Fern{\'a}ndez and Santiago Aja-Fern{\'a}ndez and Jos{\'e} M. Benlloc and Joseba Alonso} } @article {913, title = {Simultaneous imaging of hard and soft biological tissues in a low-field dental MRI scanner}, journal = {Scientific Reports}, volume = {10}, year = {2020}, month = {2021}, pages = {1{\textendash}14}, author = {Algarin, Jose M and Diaz-Caballero, Elena and Borreguero, Jose and Galve, Fernando and Grau-Ruiz, Daniel and Rigla, Juan P and Bosch, Ruben and Gonzalez, Jose M and Pallas, Eduardo and Corberan, Miguel and Carlos Gramage and Santiago Aja-Fern{\'a}ndez and Alfonso R{\'\i}os and Jos{\'e} M. Benlloch and Joseba Alonso} } @article {martinez2020smartphone, title = {Smartphone-based object recognition with embedded machine learning intelligence for unmanned aerial vehicles}, journal = {Journal of Field Robotics}, volume = {37}, number = {3}, year = {2020}, pages = {404{\textendash}420}, author = {Martinez-Alpiste, Ignacio and Pablo Casaseca-de-la-Higuera and Jose-Maria Alcaraz-Calero and Grecos, Christos and Wang, Qi} } @article {826, title = {Structural connectivity alterations in chronic and episodic migraine: A diffusion magnetic resonance imaging connectomics study}, journal = {Cephalalgia}, volume = {40}, year = {2020}, pages = {367-383}, abstract = {

OBJECTIVE:

To identify possible structural connectivity alterations in patients with episodic and chronic migraine using magnetic resonance imaging data.

METHODS:

Fifty-four episodic migraine, 56 chronic migraine patients and 50 controls underwent T1-weighted and diffusion-weighted magnetic resonance imaging acquisitions. Number of streamlines (trajectories of estimated fiber-tracts), mean fractional anisotropy, axial diffusivity and radial diffusivity were the connectome measures. Correlation analysis between connectome measures and duration and frequency of migraine was performed.

RESULTS:

Higher and lower number of streamlines were found in connections involving regions like the superior frontal gyrus when comparing episodic and chronic migraineurs with controls (p \< .05 false discovery rate). Between the left caudal anterior cingulate and right superior frontal gyri, more streamlines were found in chronic compared to episodic migraine. Higher and lower fractional anisotropy, axial diffusivity, and radial diffusivity were found between migraine groups and controls in connections involving regions like the hippocampus. Lower radial diffusivity and axial diffusivity were found in chronic compared to episodic migraine in connections involving regions like the putamen. In chronic migraine, duration of migraine was positively correlated with fractional anisotropy and axial diffusivity.

CONCLUSIONS:

Structural strengthening of connections involving subcortical regions associated with pain processing and weakening in connections involving cortical regions associated with hyperexcitability may coexist in migraine

}, keywords = {Magnetic resonance imaging (MRI), Migraine, chronic migraine, connectomics, diffusion-weighted imaging, tractography}, doi = {10.1177/0333102419885392}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Rodrigo de Luis-Garc{\'\i}a} } @article {san2020two, title = {Two-stage memetic algorithm for blind equalisation in direct-sequence/code-division multiple-access systems}, journal = {IET Communications}, year = {2020}, publisher = {IET Digital Library}, author = {San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {841, title = {A Web-Based Educational Magnetic Resonance Simulator: Design, Implementation and Testing}, journal = {Journal of Medical Systems}, volume = {44}, year = {2020}, month = {2020}, pages = {9}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Bote-Lorenzo, Miguel L and S{\'a}nchez, Eduardo G{\'o}mez and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {866, title = {Weed Classification for Site-Specific Weed Management Using an Automated Stereo Computer-Vision Machine-Learning System in Rice Fields}, journal = {Plants}, volume = {9}, year = {2020}, pages = {559}, abstract = {Site-specific weed management and selective application of herbicides as eco-friendly techniques are still challenging tasks to perform, especially for densely cultivated crops, such as rice. This study is aimed at developing a stereo vision system for distinguishing between rice plants and weeds and further discriminating two types of weeds in a rice field by using artificial neural networks (ANNs) and two metaheuristic algorithms. For this purpose, stereo videos were recorded across the rice field and different channels were extracted and decomposed into the constituent frames. Next, upon pre-processing and segmentation of the frames, green plants were extracted out of the background. For accurate discrimination of the rice and weeds, a total of 302 color, shape, and texture features were identified. Two metaheuristic algorithms, namely particle swarm optimization (PSO) and the bee algorithm (BA), were used to optimize the neural network for selecting the most effective features and classifying different types of weeds, respectively. Comparing the proposed classification method with the K-nearest neighbors (KNN) classifier, it was found that the proposed ANN-BA classifier reached accuracies of 88.74\% and 87.96\% for right and left channels, respectively, over the test set. Taking into account either the arithmetic or the geometric means as the basis, the accuracies were increased up to 92.02\% and 90.7\%, respectively, over the test set. On the other hand, the KNN suffered from more cases of misclassification, as compared to the proposed ANN-BA classifier, generating an overall accuracy of 76.62\% and 85.59\% for the classification of the right and left channel data, respectively, and 85.84\% and 84.07\% for the arithmetic and geometric mean values, respectively.}, doi = {https://doi.org/10.3390/plants9050559}, url = {https://www.mdpi.com/2223-7747/9/5/559}, author = {Dadashzadeh, Mojtaba and Yousef Abbaspour-Gilandeh and Mesri-Gundoshmian, Tarahom and Sabzi, Sajad and Hern{\'a}ndez-Hern{\'a}ndez, Jose Luis and Hern{\'a}ndez-Hern{\'a}ndez, Mario and J I Arribas} } @article {837, title = {White matter changes in chronic and episodic migraine: a diffusion tensor imaging study}, journal = {The Journal of Headache and Pain}, volume = {21}, year = {2020}, pages = {1}, chapter = {1}, abstract = {

BACKGROUND:

White matter alterations have been observed in patients with migraine. However, no microstructural white matter alterations have been found particularly in episodic or chronic migraine patients, and there is limited research focused on the comparison between these two groups of migraine patients.

METHODS:

Fifty-one healthy controls, 55 episodic migraine patients and 57 chronic migraine patients were recruited and underwent brain T1-weighted and diffusion-weighted MRI acquisition. Using Tract-Based Spatial Statistics (TBSS), fractional anisotropy, mean diffusivity, radial diffusivity and axial diffusivity were compared between the different groups. On the one hand, all migraine patients were compared against healthy controls. On the other hand, patients from each migraine group were compared between them and also against healthy controls. Correlation analysis between clinical features (duration of migraine in years, time from onset of chronic migraine in months, where applicable, and headache and migraine frequency, where applicable) and Diffusion Tensor Imaging measures was performed.

RESULTS:

Fifty healthy controls, 54 episodic migraine and 56 chronic migraine patients were finally included in the analysis. Significant decreased axial diffusivity (p \< .05 false discovery rate and by number of contrasts corrected) was found in chronic migraine compared to episodic migraine in 38 white matter regions from the Johns Hopkins University ICBM-DTI-81 White-Matter Atlas. Significant positive correlation was found between time from onset of chronic migraine and mean fractional anisotropy in the bilateral external capsule, and negative correlation between time from onset of chronic migraine and mean radial diffusivity in the bilateral external capsule.

CONCLUSIONS:

These findings suggest global white matter structural differences between episodic migraine and chronic migraine. Patients with chronic migraine could present axonal integrity impairment in the first months of chronic migraine with respect to episodic migraine patients. White matter changes after the onset of chronic migraine might reflect a set of maladaptive plastic changes.

}, keywords = {Diffusion tensor imaging, Magnetic resonance imaging (MRI), Migraine, Tract-based spatial statistics, chronic migraine}, doi = {10.1186/s10194-019-1071-3}, url = {https://thejournalofheadacheandpain.biomedcentral.com/articles/10.1186/s10194-019-1071-3}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Rodrigo de Luis-Garc{\'\i}a} } @article {867, title = {An automatic visible-range video weed detection, segmentation and classification prototype in potato field}, journal = {Heliyon}, volume = {6}, year = {2020}, pages = {e03685}, abstract = {Weeds might be defined as destructive plants that grow and compete with agricultural crops in order to achieve water and nutrients. Uniform spray of herbicides is nowadays a common cause in crops poisoning, environment pollution and high cost of herbicide consumption. Site-specific spraying is a possible solution for the problems that occur with uniform spray in fields. For this reason, a machine vision prototype is proposed in this study based on video processing and meta-heuristic classifiers for online identification and classification of Marfona potato plant (Solanum tuberosum) and 4299 samples from five weed plant varieties: Malva neglecta (mallow), Portulaca oleracea (purslane), Chenopodium album L (lamb{\textquoteright}s quarters), Secale cereale L (rye) and Xanthium strumarium (coklebur). In order to properly train the machine vision system, various videos taken from two Marfona potato fields within a surface of six hectares are used. After extraction of texture features based on the gray level co-occurrence matrix (GLCM), color features, spectral descriptors of texture, moment invariants and shape features, six effective discriminant features were selected: the standard deviation of saturation (S) component in HSV color space, difference of first and seventh moment invariants, mean value of hue component (H) in HSI color space, area to length ratio, average blue-difference chrominance (Cb) component in YCbCr color space and standard deviation of in-phase (I) component in YIQ color space. Classification results show a high accuracy of 98\% correct classification rate (CCR) over the test set, being able to properly identify potato plant from previously mentioned five different weed varieties. Finally, the machine vision prototype was tested in field under real conditions and was able to properly detect, segment and classify weed from potato plant at a speed of up to 0.15 m/s.}, doi = {https://doi.org/10.1016/j.heliyon.2020.e03685}, url = {https://www.sciencedirect.com/science/article/pii/S2405844020305302}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @article {san2020new, title = {A new flower pollination algorithm for equalization in synchronous DS/CDMA multiuser communication systems}, journal = {Soft Computing}, year = {2020}, month = {2000}, pages = {1{\textendash}15}, publisher = {Springer Berlin Heidelberg}, author = {San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {863, title = {A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value}, journal = {Measurement}, volume = {152}, year = {2020}, pages = {107298}, abstract = {An automatic 3-variety computer vision orange fruit pH value assessment system in the visible-range is presented, including each 100 different color images from Bam, Blood and Thomson orange of which the true pH has been measured and is known in advance. A total of 452 features are extracted from segmented orange color images. Results with repeated trials include: true versus estimated mean pH values, true minus estimated pH values boxplots, fitness regression dispersion plots and various error measure boxplots, for both single orange variety as well as the three-orange varieties altogether (test set), showing consistent results over all three orange varieties. Regression coefficient for pH estimation in Bam, Blood and Thomson orange varieties, were 0.950, 0.935 and 0.957, respectively. Results show that the hybrid ANN-ABC estimates pH values in orange quite similarly among orange varieties, implying that properly pH values estimation is possible for different orange varieties, regardless of orange type.}, doi = {https://doi.org/10.1016/j.measurement.2019.107298}, url = {https://www.sciencedirect.com/science/article/pii/S0263224119311625}, author = {Sabzi, Sajad and Javadikia, Hossein and J I Arribas} } @article {805, title = {Air Infiltration Monitoring using Thermography and Neural Networks}, journal = {Energy and Buildings}, volume = {191}, year = {2019}, month = {05/2019}, pages = {187-199}, chapter = {187}, author = {A Royuela and M A Padilla-Marcos and A Meiss and Pablo Casaseca-de-la-Higuera and J Feij{\'o}-Mu{\~n}oz} } @article {862, title = {An Automatic Non-Destructive Method for the Classification of the Ripeness Stage of Red Delicious Apples in Orchards Using Aerial Video}, journal = {Agronomy}, volume = {9}, year = {2019}, abstract = {The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for detecting water stress and determining the water applied during irrigation. Additionally, they can also be related to the crop coefficient (Kc) of seasonal water needs. The purpose of this research is to develop a new computer vision algorithm to detect the existing fruits in aerial images of an apple cultivar (of Red Delicious variety) and estimate their ripeness stage among four possible classes: unripe, half-ripe, ripe, and overripe. The proposed method is based on a combination of the most effective color features and a classifier based on artificial neural networks optimized with genetic algorithms. The obtained results indicate an average classification accuracy of 97.88\%, over a dataset of 8390 images and 27,687 apples, and values of the area under the ROC (receiver operating characteristic) curve near or above 0.99 for all classes. We believe this is a remarkable performance that allows a proper non-intrusive estimation of ripening that will help to improve harvesting strategies.}, doi = {https://doi.org/10.3390/agronomy9020084}, url = {https://www.mdpi.com/2073-4395/9/2/84}, author = {S Sabzi and Yousef Abbaspour-Gilandeh and G Garcia-Mateos and A Ruiz-Canales and J M Molina-Martinez and J I Arribas} } @conference {martinez2019benchmarking, title = {Benchmarking Machine-Learning-Based Object Detection on a UAV and Mobile Platform}, booktitle = {2019 IEEE Wireless Communications and Networking Conference (WCNC)}, year = {2019}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Martinez-Alpiste, Ignacio and Pablo Casaseca-de-la-Higuera and Jose-Maria Alcaraz-Calero and Grecos, Christos and Wang, Qi} } @article {816, title = {Computation of exact g-factor maps in 3D GRAPPA reconstructions}, journal = {Magnetic resonance in medicine}, volume = {81}, year = {2019}, pages = {1353{\textendash}1367}, author = {I{\~n}aki Rabanillo-Viloria and Zhu, Ante and Santiago Aja-Fern{\'a}ndez and Alberola-L{\'o}pez, Carlos and Hernando, Diego} } @article {802, title = {Efficient QoE-Aware Scheme for Video Quality Switching Operations in Dynamic Adaptive Streaming}, journal = {ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)}, volume = {15}, year = {2019}, pages = {17}, author = {Irondi, Iheanyi and Wang, Qi and Grecos, Christos and Calero, Jose M Alcaraz and Pablo Casaseca-de-la-Higuera} } @conference {hoyos2019evaluation, title = {Evaluation in a real environment of a trainable cough monitoring app for smartphones}, booktitle = {Mediterranean Conference on Medical and Biological Engineering and Computing}, year = {2019}, pages = {1175{\textendash}1180}, publisher = {Springer, Cham}, organization = {Springer, Cham}, author = {Hoyos-Barcel{\'o}, Carlos and Garmendia-Leiza, Jos{\'e} Ram{\'o}n and MD Aguilar-Garcia and Monge-{\'A}lvarez, Jes{\'u}s and P{\'e}rez-Alonso, Diego Asay and Alberola-L{\'o}pez, Carlos and Pablo Casaseca-de-la-Higuera} } @article {801, title = {A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {66}, year = {2019}, pages = {2319-2330}, author = {Monge-Alvarez, Jesus and Hoyos-Barcelo, Carlos and San Jose-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @proceedings {810, title = {Motion-Robust and Blood-Suppressed M1-Optimized Diffusion MR Imaging of the Liver}, volume = {116}, year = {2019}, abstract = {

Liver DWI has been shown to enable the detection, characterization and treatment monitoring of focal liver lesions, as well as the assessment of diffuse liver disease (eg: fibrosis and cirrhosis)1,2. However, liver DWI is challenging because of the relatively short T2 of liver tissue and the motion sensitivity of diffusion encoding sequences3,4. Recently, advanced motion-robust DW gradient waveform design techniques5-7 enabled first motion moment-nulled (M1-nulled) and/or second motion moment nulled (M2-nulled) DWI with optimized echo time (TE). However, these motion moment-nulled gradient waveforms also compensate the signal from moving blood, which is nulled in standard liver DWI. Importantly, non-suppressed blood signal can mimic focal liver lesions and may confound the assessment and detection of true focal lesions in DWI, as well as introduce bias and variability in quantitative diffusion measures. Consequently, the lack of blood suppression in motion moment-nulled DWI techniques may hinder their clinical applicability for liver DWI.

}, author = {Yuxin Zhang and {\'O}scar Pe{\~n}a-Nogales and James H. Holmes and Diego Hernando} } @conference {jimenez2019novel, title = {A Novel Design Method for Digital FIR/IIR Filters Based on the Shuffle Frog-Leaping Algorithm}, booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)}, year = {2019}, pages = {1{\textendash}5}, publisher = {IEEE}, organization = {IEEE}, author = {Jim{\'e}nez-Galindo, Daniel and Pablo Casaseca-de-la-Higuera and San-Jos{\'e}-Revuelta, Luis M} } @article {807, title = {OpenCLIPER: An OpenCL-Based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices}, journal = {IEEE Journal of Biomedical and Health Informatics}, volume = {23}, year = {2019}, month = {July}, pages = {1702-1709}, abstract = {

Medical image processing is often limited by the computational cost of the involved algorithms. Whereas dedicated computing devices (GPUs in particular) exist and do provide significant efficiency boosts, they have an extra cost of use in terms of housekeeping tasks (device selection and initialization, data streaming, synchronization with the CPU, and others), which may hinder developers from using them. This paper describes an OpenCL-based framework that is capable of handling dedicated computing devices seamlessly and that allows the developer to concentrate on image processing tasks. The framework handles automatically device discovery and initialization, data transfers to and from the device and the file system and kernel loading and compiling. Data structures need to be defined only once independently of the computing device; code is unique, consequently, for every device, including the host CPU. Pinned memory/buffer mapping is used to achieve maximum performance in data transfers. Code fragments included in the paper show how the computing device is almost immediately and effortlessly available to the users algorithms, so they can focus on productive work. Code required for device selection and initialization, data loading and streaming and kernel compilation is minimal and systematic. Algorithms can be thought of as mathematical operators (called processes), with input, output and parameters, and they may be chained one after another easily and efficiently. Also for efficiency, processes can have their initialization work split from their core workload, so process chains and loops do not incur in performance penalties. Algorithm code is independent of the device type targeted.

}, keywords = {C++, C++ languages, Data structures, GPU, Graphics processing units, Image reconstruction, Informatics, Kernel, Libraries, Medical imaging, OpenCL}, issn = {2168-2194}, doi = {10.1109/JBHI.2018.2869421}, author = {Federico Simmross-Wattenberg and M. Rodr{\'\i}guez-Cayetano and J Royuela-del-Val and E. Mart{\'\i}n-Gonz{\'a}lez and E. Moya-S{\'a}ez and M. Mart{\'\i}n-Fern{\'a}ndez and C. Alberola-L{\'o}pez} } @article {817, title = {Optimized Diffusion-Weighting Gradient Waveform Design (ODGD) formulation for motion compensation and concomitant gradient nulling}, journal = {Magnetic resonance in medicine}, volume = {81}, year = {2019}, pages = {989{\textendash}1003}, author = {{\'O}scar Pe{\~n}a-Nogales and Zhang, Yuxin and Wang, Xiaoke and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Holmes, James H and Hernando, Diego} } @article {861, title = {An Outdoors Multi-stage Fruit-tree Orchard Video Image Segmentation System under Natural Conditions}, journal = {Journal of Agricultural Sciences}, volume = {25}, year = {2019}, chapter = {427}, abstract = {Segmentation is an important part of each machine vision system that has a direct relationship with the final system accuracy and performance. Outdoors segmentation is often complex and difficult due to both changes in sunlight intensity and the different nature of background objects. However, in fruit-tree orchards, an automatic segmentation algorithm with high accuracy and speed is very desirable. For this reason, a multi-stage segmentation algorithm is applied for the segmentation of apple fruits with Red Delicious cultivar in orchard under natural light and background conditions. This algorithm comprises a combination of five segmentation stages, based on: 1- L*u*v* color space, 2- local range texture feature, 3- intensity transformation, 4- morphological operations, and 5- RGB color space. To properly train a segmentation algorithm, several videos were recorded under nine different light intensities in Iran-Kermanshah (longitude: 7.03E; latitude: 4.22N) with natural (real) conditions in terms of both light and background. The order of segmentation stage methods in multi-stage algorithm is very important since has a direct relationship with final segmentation accuracy. The best order of segmentation methods resulted to be: 1- color, 2- texture and 3- intensity transformation methods. Results show that the values of sensitivity, accuracy and specificity, in both classes, were higher than 97.5\%, over the test set. We believe that those promising numbers imply that the proposed algorithm has a remarkable performance and could potentially be applied in real-world industrial case.}, doi = {https://doi.org/10.15832/ankutbd.434137}, url = {https://dergipark.org.tr/en/pub/ankutbd/issue/50426/434137}, author = {Yousef Abbaspour-Gilandeh and Sajad Sabzi and J I Arribas} } @article {menchon2019reconstruction, title = {Reconstruction techniques for cardiac cine MRI}, journal = {Insights into imaging}, volume = {10}, number = {1}, year = {2019}, pages = {100}, publisher = {Springer Berlin Heidelberg}, author = {Mench{\'o}n-Lara, Rosa-Mar{\'\i}a and Simmross-Wattenberg, Federico and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Alberola-L{\'o}pez, Carlos} } @proceedings {809, title = {Reduced Eddy Current induced image distortions and Peripheral Nerve Stimulation based on the Optimal Diffusion-weighting Gradient Waveform Design (ODGD) formulation}, volume = {3488}, year = {2019}, abstract = {

Diffusion-Weighted MRI (DW-MRI) often suffers from signal attenuation due to long TE, motion-related artefacts, dephasing due to concomitant gradients (CGs), and image distortions due to eddy currents (ECs). Further, the application of rapidly switching gradients may cause peripheral nerve stimulation (PNS). These challenges hinder the progress, application and interpretability of DW-MRI. Therefore, based on the Optimized Diffusion-weighting Gradient waveforms Design (ODGD) formulation, in this work we design optimal (minimum TE) nth-order moment-nulling diffusion-weighting gradient waveforms with or without CG-nulling able to reduce EC induced distortions and PNS-effects. We assessed the feasibility of these waveforms in simulations and phantom experiments.

}, author = {{\'O}scar Pe{\~n}a-Nogales and Yuxin Zhang and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and James H. Holmes and Diego Hernando} } @inbook {818, title = {Return-to-Axis Probability Calculation from Single-Shell Acquisitions}, booktitle = {Computational Diffusion MRI}, year = {2019}, pages = {29-41}, publisher = {Springer}, organization = {Springer}, isbn = {978-3-030-05830-2}, doi = {10.1007/978-3-030-05831-9_3}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Molendowska, Malwina and Tomasz Pieciak and Luis-Garc{\'\i}a, Rodrigo} } @article {803, title = {Robust detection of audio-cough events using local Hu moments}, journal = {IEEE journal of biomedical and health informatics}, volume = {23}, year = {2019}, pages = {184{\textendash}196}, author = {Monge-{\'A}lvarez, Jes{\'u}s and Hoyos-Barcel{\'o}, Carlos and Lesso, Paul and Pablo Casaseca-de-la-Higuera} } @article {796, title = {A Second Order Multi-Stencil Fast Marching Method With a Non-Constant Local Cost Model}, journal = {IEEE Transactions on Image Processing}, volume = {28}, year = {2019}, month = {04/2019}, pages = {1967{\textendash}1979}, abstract = {

The fast marching method is widely employed in several fields of image processing. Some years ago a multi-stencil version (MSFM) was introduced to improve its accuracy by solving the equation for a set of stencils and choosing the best solution at each considered node. The following work proposes a modified numerical scheme for MSFM to take into account the variation of the local cost, which has proven to be second order. The influence of the stencil set choice on the algorithm outcome with respect to stencil orthogonality and axis swapping is also explored, where stencils are taken from neighborhoods of varying radius. The experimental results show that the proposed schemes improve the accuracy of their original counterparts, and that the use of permutation-invariant stencil sets provides robustness against shifted vector coordinates in the stencil set.

}, keywords = {Approximation algorithms, Differential equations, Eikonal equation, Frequency modulation, MSFM, Mathematical model, Silicon, Three-dimensional displays, Unmanned aerial vehicles, Vectors, axis swapping, difference equations, fast marching methods, finite difference methods, finite differences, image processing, iterative methods, least squares approximations, multi-stencil schemes, multistencil version, nonconstant local cost model, permutation-invariant stencil sets, second order multistencil fast marching method, stencil orthogonality, stencil set}, issn = {1057-7149}, doi = {10.1109/TIP.2018.2880507}, url = {https://ieeexplore.ieee.org/document/8531783/}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and M. T. P{\'e}rez and Pablo Casaseca-de-la-Higuera and M. Mart{\'\i}n-Fern{\'a}ndez and R. Deriche and C. Alberola-L{\'o}pez} } @conference {815, title = {Single-Shell Return-to-the-Origin Probability Diffusion Mri Measure Under a Non-Stationary Rician Distributed Noise}, booktitle = {2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)}, year = {2019}, publisher = {IEEE}, organization = {IEEE}, author = {Tomasz Pieciak and Bogusz, Fabian and Antonio Trist{\'a}n-Vega and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez} } @article {795, title = {Space-time variant weighted regularization in compressed sensing cardiac cine MRI}, journal = {Magnetic Resonance Imaging}, volume = {58}, year = {2019}, pages = {44 - 55}, abstract = {

Purpose: To analyze the impact on image quality and motion fidelity of a motion-weighted space-time variant regularization term in compressed sensing cardiac cine MRI.
Methods: k-t SPARSE-SENSE with temporal total variation (tTV) is used as the base reconstruction algorithm. Motion in the dynamic image is estimated by means of a robust registration technique for non-rigid motion. The resulting deformation fields are used to leverage the regularization term. The results are compared with standard k-t SPARSE-SENSE with tTV regularization as well as with an improved version of this algorithm that makes use of tTV and temporal Fast Fourier Transform regularization in x-f domain.
Results: The proposed method with space-time variant regularization provides higher motion fidelity and image quality than the two previously reported methods. Difference images between undersampled reconstruction and fully sampled reference images show less systematic errors with the proposed approach.
Conclusions: Usage of a space-time variant regularization offers reconstructions with better image quality than the state of the art approaches used for comparison.

}, keywords = {Cine cardiac MRI, Space-time variant regularization, compressed sensing, k-t SPARSE-SENSE}, issn = {0730-725X}, doi = {https://doi.org/10.1016/j.mri.2019.01.005}, url = {http://www.sciencedirect.com/science/article/pii/S0730725X18301978}, author = {Alejandro Godino-Moya and J Royuela-del-Val and Muhammad Usman and Rosa-Mar{\'\i}a Mench{\'o}n-Lara and Marcos Mart{\'\i}n-Fern{\'a}ndez and Claudia Prieto and Carlos Alberola-L{\'o}pez} } @conference {821, title = {White Matter Alterations in Chronic Migraine: A Diffusion Tensor Imaging and Structural Connectivity Study}, booktitle = {19th International Headache Congress International Headache Society}, year = {2019}, month = {2019}, publisher = {Cephalalgia}, organization = {Cephalalgia}, address = {Dublin, Ireland}, abstract = {

Objective: White matter alterations have been observed in patients with migraine. However, no microstructural white matter alterations have been found particularly in Episodic Migraine (EM) with respect to Chronic Migraine (CM) patients. In this study, we investigated whether there are significant differences between EM and CM, and between these groups and healthy controls, using diffusion Magnetic Resonance Imaging (dMRI) data.
Methods: We acquired high-resolution 3D brain T1-weighted and dMRI from 51 Healthy Controls (HC), 55 EM patients and 57 CM patients. Using Tract-Based Spatial Statistics, we compared Fractional Anisotropy (FA), Mean Diffusivity (MD), Radial Diffusivity (RD) and Axial Diffusivity (AD) between the different groups. We also obtained structural connectome matrices for each subject employing both dMRI and T1-weighted acquisitions. Number of streamlines, mean FA and mean AD for each white matter connection were compared between the three groups.
Results: Significant decreased AD (p \<.05 Family Wise Error corrected and volume \>30 mm3) were found in CM compared to EM in 38 white matter regions. Significant differences in the number of streamlines were found in 18 connections from the connectome when comparing migraine patients with healthy controls (p \<.05 False Discovery Rate corrected); significant differences were also found between CM and EM in one of these connections. Furthermore, significant differences in FA and AD were found in three and four connections from the connectome respectively (p \<.05 False Discovery Rate corrected); significant differences were also found between CM and EM in two of AD connections.
Conclusion: Our findings suggest global white matter structural differences between EM and CM, and structural connectivity alterations in migraine patients with respect to healthy controls, and in CM compared to EM.
Disclosure of Interest: None Declared.

}, doi = {https://doi.org/10.1177/0333102419859835}, url = {https://journals.sagepub.com/doi/full/10.1177/0333102419859835}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}ngel L. Guerrero and Santiago Aja-Fern{\'a}ndez and Rodr{\'\i}guez, Margarita and Rodrigo de Luis-Garc{\'\i}a} } @article {769, title = {Audio-cough event detection based on moment theory}, journal = {Applied Acoustics}, volume = {135}, year = {2018}, pages = {124{\textendash}135}, author = {Monge-{\'A}lvarez, Jes{\'u}s and Hoyos-Barcel{\'o}, Carlos and Dahal, Keshav and Pablo Casaseca-de-la-Higuera} } @conference {752, title = {Bias Correction for Non-Stationary Noise Filtering in MRI}, booktitle = {2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI)}, year = {2018}, month = {2018}, address = {Washington DC}, author = {Tomasz Pieciak and I{\~n}aki Rabanillo-Viloria and Santiago Aja-Fern{\'a}ndez} } @article {772, title = {Characterisation of Received Signal Strength Perturbations using Allan Variance}, journal = {IEEE Transactions on Aerospace and Electronic Systems}, volume = {54}, year = {2018}, pages = {873-889}, chapter = {873}, author = {Luo, Chunbo and Pablo Casaseca-de-la-Higuera and McClean, Sally and Parr, Gerard and Ren, Peng} } @conference {800, title = {Compressed UAV sensing for flood monitoring by solving the continuous travelling salesman problem over hyperspectral maps}, booktitle = {Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2018}, year = {2018}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Pablo Casaseca-de-la-Higuera and Antonio Trist{\'a}n-Vega and Hoyos-Barcel{\'o}, Carlos and S. Merino-Caviedes and Wang, Qi and Luo, Chunbo and Wang, Xinheng and Wang, Zhi} } @conference {791, title = {On the Construction of Non Linear Adjoint Operators: Application to L1-Penalty Dynamic Image Reconstruction}, booktitle = {Congreso Anual de Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2018}, month = {11/2018}, address = {Ciudad Real, Espa{\~n}a}, abstract = {

The purpose of this work is to develop a methodology for the adjoint operators application in non linear optimization problems. The use of adjoint operators is very popular for numerical control theory; one of its main applications is devised for image reconstruction. Most of these reconstruction techniques are limited to linear L1-constraints whose adjoints are well-defined. We aim to extend these image reconstruction techniques allowing the terms involved to be non linear. For these purpose, we have generalized the concept of adjoint operator under the basis of Taylor{\textquoteright}s formula, using Gateaux derivatives in order to construct a linearised adjoint operator associated to the non linear operator. The proposed approach has been validated in a Magnetic Resonance Imaging (MRI) reconstruction framework with Cartesian subsampled k-space data using Compressed Sensing based techniques and a groupwise registration algorithm for motion compensation.
The proposed algorithm has shown to be able to effectively deal with the presence of both physiological motion and subsampling artefacts, increasing accuracy and robustness of the reconstruction as compared with its linear counterpart.

}, author = {Santiago Sanz-Est{\'e}banez and Elisa Moya-S{\'a}ez and J Royuela-del-Val and Carlos Alberola-L{\'o}pez} } @article {799, title = {Efficient computation of image moments for robust cough detection using smartphones}, journal = {Computers in biology and medicine}, volume = {100}, year = {2018}, pages = {176{\textendash}185}, author = {Hoyos-Barcel{\'o}, Carlos and Monge-{\'A}lvarez, Jes{\'u}s and Pervez, Zeeshan and San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {771, title = {Efficient k-NN Implementation for Real-Time Detection of Cough Events in Smartphones}, journal = {IEEE Journal of Biomedical and Health Informatics}, volume = {23}, year = {2018}, pages = {1662-1671}, chapter = {1662}, author = {Hoyos-Barcel{\'o}, Carlos and Monge-{\'A}lvarez, Jes{\'u}s and Shakir, Muhammad Zeeshan and Jose-Maria Alcaraz-Calero and Pablo Casaseca-de-la-Higuera} } @article {736, title = {Exact Calculation of Noise Maps and g-Factor in GRAPPA using a k-space Analysis}, journal = {IEEE Transactions on Medical Imaging}, volume = {37}, year = {2018}, month = {2018}, pages = {480-490}, chapter = {480}, issn = {0278-0062}, doi = {10.1109/TMI.2017.2760921}, author = {I{\~n}aki Rabanillo-Viloria and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Diego Hernando} } @inbook {755, title = {Introduction to speckle filtering}, booktitle = {Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video}, year = {2018}, publisher = {IET}, organization = {IET}, chapter = {5}, issn = {978-1-78561-290-9}, author = {Gabriel Ramos-Llord{\'e}n and Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @article {733, title = {Joint Groupwise Registration and ADC Estimation in the Liver using a B-Value Weighted Metric}, journal = {Magnetic Resonance Imaging}, volume = {46}, year = {2018}, month = {2018}, pages = {1-8}, type = {Original Contribution}, chapter = {1}, abstract = {

The purpose of this work is to develop a groupwise elastic multimodal registration algorithm for robust ADC estimation in the liver on multiple breath hold diffusion weighted images.

We introduce a joint formulation to simultaneously solve both the registration and the estimation problems. In order to avoid non-reliable transformations and undesirable noise amplification, we have included appropriate smoothness constraints for both problems. Our metric incorporates the ADC estimation residuals, which are inversely weighted according to the signal content in each diffusion weighted image.

Results show that the joint formulation provides a statistically significant improvement in the accuracy of the ADC estimates. Reproducibility has also been measured on real data in terms of the distribution of ADC differences obtained from different\ b-values\ subsets.\ 

The proposed algorithm is able to effectively deal with both the presence of motion and the geometric distortions, increasing accuracy and reproducibility in diffusion parameters estimation.

}, keywords = {ADC Estimation, Diffusion Weighted Imaging, Groupwise Registration, Joint Optimization, Residual Minimization Metric}, doi = {https://doi.org/10.1016/j.mri.2017.10.002}, url = {http://www.sciencedirect.com/science/article/pii/S0730725X17302187}, author = {Santiago Sanz-Est{\'e}banez and I{\~n}aki Rabanillo-Viloria and J Royuela-del-Val and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {784, title = {Joint Image Reconstruction and Phase Corruption Maps Estimation in Multi-Shot Echo Planar Imaging}, booktitle = {MICCAI}, year = {2018}, month = {09/2018}, publisher = {MICCAI}, organization = {MICCAI}, address = {Granada}, abstract = {

Multishot echo-planar imaging is a common strategy in diffusion Magnetic Resonance Imaging to reduce the artifacts caused by the long echo-trains in single-shot acquisitions. However, it su ers from shot-to-shot phase discrepancies associated to subject motion, which can notably degrade the quality of the reconstructed image. Consequently, some
type of motion-induced phases error correction needs to be incorporated into the reconstruction process. In this paper we focus on ridig motion induced errors, which have proved to corrupt the shots with linear phase maps. By incorporating this prior knowledge, we propose a maximum likelihood formulation that estimates both the parameters that characterize the linear phase maps and the reconstructed image. In order to make the problem tractable, we follow a greedy iterative procedure that alternates between the estimation of each of them. Simulation data are used to illustrate the performance of the method against state-of-the-art alternatives.

}, author = {I{\~n}aki Rabanillo-Viloria and Santiago Sanz-Est{\'e}banez and Santiago Aja-Fern{\'a}ndez and Joseph V. Hajnal and Carlos Alberola-L{\'o}pez and Lucilio Cordero-Grande} } @article {794, title = {Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson{\textquoteright}s Disease}, journal = {Frontiers in Neuroscience}, volume = {12}, year = {2018}, pages = {967}, author = {{\'O}scar Pe{\~n}a-Nogales and Ellmore, Timothy Michael and Rodrigo de Luis-Garc{\'\i}a and Suescun, Jessika and Schiess, Mya Caryn and Giancardo, Luca} } @conference {804, title = {Mapping Raw Acceleration Data on ActiGraph Counts: A Machine Learning Approach}, booktitle = {Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality}, year = {2018}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {ActiGraph, Actimetry, Microsoft Band 2, counts}, isbn = {978-1-4503-6518-5}, doi = {10.1145/3284179.3284260}, url = {http://doi.acm.org/10.1145/3284179.3284260}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Rodrigo de Luis-Garc{\'\i}a and Pablo Casaseca-de-la-Higuera and Garmendia-Leiza, J. R. and Jesus Maria Andres-de-Llano and Alberola-L{\'o}pez, Carlos} } @inbook {756, title = {Nonlinear despeckle filtering}, booktitle = {Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video}, year = {2018}, publisher = {IET}, organization = {IET}, chapter = {8}, issn = {978-1-78561-290-9}, author = {Santiago Aja-Fern{\'a}ndez and Gabriel Ramos-Llord{\'e}n and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @proceedings {760, title = {Optimal Diffusion-weighting Gradient Waveform Design (ODGD): Formulation and Experimental Validation}, year = {2018}, pages = {685}, address = {Paris, France}, author = {{\'O}scar Pe{\~n}a-Nogales and Yuxin Zhang and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and James H. Holmes and Diego Hernando} } @article {793, title = {Optimized Diffusion-Weighting Gradient Waveform Design (ODGD) formulation for motion compensation and concomitant gradient nulling}, journal = {Magnetic resonance in medicine}, year = {2018}, author = {{\'O}scar Pe{\~n}a-Nogales and Zhang, Yuxin and Wang, Xiaoke and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Holmes, James H and Hernando, Diego} } @proceedings {759, title = {Return-to-the-origin probability calculation in single shell acquisitions}, year = {2018}, pages = {1414}, address = {Paris, France}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Malwina Molendowska and Tomasz Pieciak and Rodrigo de Luis-Garc{\'\i}a} } @article {779, title = {Robust Estimation of the Apparent Diffusion Coefficient Invariant to Acquisition Noise and Physiological Motion}, journal = {Magnetic Resonance Imaging}, volume = {53}, year = {2018}, pages = {123-133}, abstract = {

In this work we have proposed a methodology for the estimation of the apparent diffusion coefficient in the body from multiple breath hold diffusion weighted images, which is robust to two preeminent confounding factors: noise and motion during acquisition. We have extended a method for the joint groupwise multimodal registration and apparent diffusion coefficient estimation, previously proposed by the authors, in order to correct the bias that arises from the non-Gaussianity of the data and the registration procedure. Results show that the proposed methodology provides a statistically significant improvement both in robustness for displacement fields calculation and in terms of accuracy for the apparent diffusion coefficient estimation as compared with traditional sequential approaches. Reproducibility has also been measured on real data in terms of the distribution of apparent diffusion coefficient differences obtained from different b-values subsets. Our proposal has shown to be able to effectively correct the estimation bias by introducing additional computationally light procedures to the original method, thus providing robust apparent diffusion coefficient maps in the liver and allowing an accurate and reproducible analysis of the tissue.

}, keywords = {Acquisition Noise, Apparent Diffusion Coefficient, Diffusion Weighted Imaging, Multimodal Groupwise Registration, Patient Movement Correction}, doi = {https://doi.org/10.1016/j.mri.2018.07.005}, url = {https://www.sciencedirect.com/science/article/pii/S0730725X18300687}, author = {Santiago Sanz-Est{\'e}banez and Tomasz Pieciak and Carlos Alberola-L{\'o}pez and Santiago Aja-Fern{\'a}ndez} } @conference {785, title = {Robust Windowed Harmonic Phase Analysis with a Single Acquisition}, booktitle = {MICCAI }, year = {2018}, month = {2018}, publisher = {MICCAI}, organization = {MICCAI}, address = {Granada}, abstract = {

The HARP methodology is a widely extended procedure for cardiac tagged magnetic resonance imaging since it is able to analyse local mechanical behaviour of the heart; extensions and improvements of this method have also been reported since HARP was released. Acquisition of an over-determined set of orientations is one of such alternatives,
which has notably increased HARP robustness at the price of increasing examination time. In this paper, we explore an alternative to this method based on the use of multiple peaks, as opposed to multiple orientations, intended for a single acquisition. Performance loss is explored with respect to multiple orientations in a real setting. In addition, we have assessed, by means of a computational phantom, optimal tag orientations and spacings of the stripe pattern by minimizing the Frobenius norm of the difference between the ground truth and the estimated material deformation gradient tensor. Results indicate that, for a single acquisition, multiple peaks as opposed to multiple orientations, are indeed preferable.

}, keywords = {Cardiac Tagged Magnetic Resonance Imaging, HARmonic Phase, Multi-Harmonic Analysis, Robust Strain Reconstruction}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Marcos Martin-Fern{\'a}ndez and Carlos Alberola L{\'o}pez} } @article {781, title = {Scalar diffusion-MRI measures invariant to acquisition parameters: A first step towards imaging biomarkers}, journal = {Magnetic Resonance Imaging}, volume = {54}, year = {2018}, month = {2018}, pages = {194 - 213}, issn = {0730-725X}, doi = {https://doi.org/10.1016/j.mri.2018.03.001}, url = {http://www.sciencedirect.com/science/article/pii/S0730725X18300262}, author = {Santiago Aja-Fern{\'a}ndez and Tomasz Pieciak and Antonio Trist{\'a}n-Vega and Gonzalo Vegas-S{\'a}nchez-Ferrero and Vicente Molina and Rodrigo de Luis-Garc{\'\i}a} } @inbook {757, title = {Techniques for tracking: image registration}, booktitle = {Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video}, year = {2018}, publisher = {IET}, organization = {IET}, chapter = {15}, issn = {978-1-78561-290-9}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {761, title = {Topography of activation deficits in schizophrenia during P300 task related to cognition and structural connectivity}, journal = {European Archives of Psychiatry and Clinical Neuroscience}, year = {2018}, month = {Feb}, issn = {1433-8491}, doi = {10.1007/s00406-018-0877-3}, url = {https://doi.org/10.1007/s00406-018-0877-3}, author = {Vicente Molina and Bachiller, Alejandro and Rodrigo de Luis-Garc{\'\i}a and Lubeiro, Alba and Poza, Jes{\'u}s and Hornero, Roberto and Alonso, Joan Francesc and Ma{\~n}anas, Miguel Angel and Marqu{\'e}s, Patricia and Romero, Sergio} } @conference {mi2018towards, title = {Towards Optimal Power Splitting in Simultaneous Power and Information Transmission}, booktitle = {2018 IEEE Global Communications Conference (GLOBECOM)}, year = {2018}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Mi, Yang and Luo, Chunbo and Min, Geyong and Pablo Casaseca-de-la-Higuera and Wang, Zhi} } @article {749, title = {Vortical Features for Myocardial Rotation Assessment in Hypertrophic Cardiomyopathy using Cardiac Tagged Magnetic Resonance}, journal = {Medical Image Analysis}, volume = {In Press}, year = {2018}, month = {04/2018}, type = {Original Article}, abstract = {

Left ventricular rotational motion is a feature of normal and diseased cardiac function. However, classical torsion and twist measures rely on the definition of a rotational axis which may not exist. This paper reviews global and local rotation descriptors of myocardial motion and introduces new curl-based (vortical) features built from tensorial magnitudes, intended to provide better comprehension about fibrotic tissue characteristics mechanical properties. Fifty-six cardiomyopathy patients and twenty-two healthy volunteers have been studied using tagged magnetic resonance by means of harmonic phase analysis. Rotation descriptors are built, with no assumption about a regular geometrical model, from different approaches. The extracted vortical features have been tested by means of a sequential cardiomyopathy classification procedure; they have proven useful for the regional characterization of the left ventricular function by showing great separability not only between pathologic and healthy patients but also, and specifically, between heterogeneous phenotypes within cardiomyopathies.

}, doi = {10.1016/j.media.2018.03.005}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and T. Sevilla-Ruiz and A. Revilla-Orodea and Rodrigo de Luis-Garc{\'\i}a and M Martin-Fernandez and Carlos Alberola-Lopez} } @article {858, title = {An automatic and non-intrusive hybrid computer vision system for the estimation of peel thickness in Thomson orange}, journal = {Spanish Journal of Agricultural Research}, volume = {16}, year = {2018}, pages = {e0204}, abstract = {Orange peel has important flavor and nutrition properties and is often used for making jam and oil in the food industry. For previous reasons, oranges with high peel thickness are valuable. In order to properly estimate peel thickness in Thomson orange fruit, based on a number of relevant image features (area, eccentricity, perimeter, length/area, blue component, green component, red component, width, contrast, texture, width/area, width/length, roughness, and length) a novel automatic and non-intrusive approach based on computer vision with a hybrid particle swarm optimization (PSO), genetic algorithm (GA) and artificial neural network (ANN) system is proposed. Three features (width/area, width/length and length/area ratios) were selected as inputs to the system. A total of 100 oranges were used, performing cross validation with 100 repeated experiments with uniform random samples test sets. Taguchi{\textquoteright}s robust optimization technique was applied to determine the optimal set of parameters. Prediction results for orange peel thickness (mm) based on the levels that were achieved by Taguchi{\textquoteright}s method were evaluated in several ways, including orange peel thickness true-estimated boxplots for the 100 orange database and various error parameters: the sum square error (SSE), the mean absolute error (MAE), the coefficient of determination (R2), the root mean square error (RMSE), and the mean square error (MSE), resulting in mean error parameter values of R2=0.854{\textpm}0.052, MSE=0.038{\textpm}0.010, and MAE=0.159{\textpm}0.023, over the test set, which to our best knowledge are remarkable numbers for an automatic and non-intrusive approach with potential application to real-time orange peel thickness estimation in the food industry. }, doi = {http://dx.doi.org/10.5424/sjar/2018164-11185}, url = {https://revistas.inia.es/index.php/sjar/article/view/11185}, author = {H Javadikia and S Sabzi and J I Arribas} } @article {859, title = {A new approach for the design of digital frequency selective FIR fillters using an FPA-based algorithm}, journal = {Expert Systems with Applications}, volume = {106}, year = {2018}, chapter = {92-106}, abstract = {Efficient digital filter design is an essential signal processing task. Finite Impulse Response (FIR) filters are used in many applications due to its properties of linear phase and frequency stability. Most traditional design methods suffer from the problem of insufficient control over the frequency response of the designed filter. For this reason, the use of a recently developed optimisation technique called flowers pollination algorithm (FPA), {\textendash}based on the natural process of pollination of flowers{\textendash} along with a novel multiple fitness function, is proposed in order to obtain optimised filter coefficients that best approximate ideal specifications. Results have been compared to both traditional methods (mainly windowing and the Parks-McClellan algorithm) as well as to several nature-inspired schemes. Finally, processing of a real EEG signal is used to quantitatively evaluate performance of designed filters. Numerical results show that our method achieves better fit to desired filter specifications, a 5-10 times larger attenuation in the stop band and a narrower transition band, at the expense of slightly increasing the pass-band ripple (5-15\%) in 3 out of 4 of the cases.}, doi = {https://doi.org/10.1016/j.eswa.2018.03.045}, url = {https://www.sciencedirect.com/science/article/pii/S095741741830191X}, author = {L M San-Jose-Revuelta and J I Arribas} } @article {768, title = {A novel infrared video surveillance system using deep learning based techniques}, journal = {Multimedia Tools and Applications}, volume = {77}, year = {2018}, chapter = {26657}, author = {Zhang, Huaizhong and Luo, Chunbo and Wang, Qi and Kitchin, Matthew and Parmley, Andrew and Monge-Alvarez, Jesus and Pablo Casaseca-de-la-Higuera} } @article {860, title = {A visible-range computer-vision system for automated, non-intrusive assessment of the pH value in Thomson oranges}, journal = {Computers In Industry}, volume = {99}, year = {2018}, chapter = {69-82} } @conference {740, title = {ADC-Weighted Joint Registration-Estimation for Cardiac Diffusion Magnetic Resonance Imaging}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2017}, month = {12/2017}, abstract = {

The purpose of this work is to develop a method for the groupwise registration of diffusion weighted datasets of the heart which automatically provide smooth Apparent Diffusion Coefficient (ADC) estimations, by making use of a novel multimodal scheme. To this
end, we have introduced a joint methodology that simultaneously performs both the alignment of the images and the ADC estimation. In order to promote diffeomorphic transformations and to avoid undesirable noise amplification, we have included appropriate
smoothness constraints for both problems under the same formulation. The implemented multimodal registration metric incorporates the ADC estimation residuals, which are inversely weighted with the b-values to balance the influence of the signal level for each diffusion weighted image. Results show that the joint formulation provides more robust and precise ADC estimations and a significant improvement in the overlap of the contour
of manual delineations along the different b-values. The proposed algorithm is able to effectively deal with the presence of both physiological motion and inherent contrast variability for the different b-value images, increasing accuracy and robustness of the estimation of diffusion parameters for cardiac imaging.

}, author = {Santiago Sanz-Est{\'e}banez and J Royuela-del-Val and Jordi Broncano-Cabrero and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {698, title = {Abnormal Capillary Vasodynamics Contribute to Ictal Neurodegeneration in Epilepsy}, journal = {Scientific Reports}, volume = {7}, year = {2017}, abstract = {

Seizure-driven brain damage in epilepsy accumulates over time, especially in the hippocampus, which can lead to sclerosis, cognitive decline, and death. Excitotoxicity is the prevalent model to explain ictal neurodegeneration. Current labeling technologies cannot distinguish between excitotoxicity and hypoxia, however, because they share common molecular mechanisms. This leaves open the possibility that undetected ischemic hypoxia, due to ictal blood flow restriction, could contribute to neurodegeneration previously ascribed to excitotoxicity. We tested this possibility with Confocal Laser Endomicroscopy (CLE) and novel stereological analyses in several models of epileptic mice. We found a higher number and magnitude of NG2+ mural-cell mediated capillary constrictions in the hippocampus of epileptic mice than in that of normal mice, in addition to spatial coupling between capillary constrictions and oxidative stressed neurons and neurodegeneration. These results reveal a role for hypoxia driven by capillary blood flow restriction in ictal neurodegeneration. {\textcopyright} 2017 The Author(s).

}, doi = {10.1038/srep43276}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014072909\&doi=10.1038\%2fsrep43276\&partnerID=40\&md5=e9d3567266bdc360a7addc92be350c8d}, author = {Leal-Campanario, R. and Alarcon-Martinez, L. and Rieiro, H. and Martinez-Conde, S. and Alarcon-Martinez, T. and Zhao, X. and LaMee, J. and Popp, P.J. and Calhoun, M.E. and J I Arribas and Schlegel, A.A. and Di Stasi, L.L. and Rho, J.M. and Inge, L. and Otero-Millan, J. and Treiman, D.M. and Macknik, S.L.} } @proceedings {723, title = {Determination of the optimal set of b-values for ADC mapping under a Rician noise assumption}, year = {2017}, pages = {3341}, address = {Honolulu, HI, USA}, abstract = {

Mapping of the apparent diffusion coefficient (ADC), estimated from a set of diffusion-weighted (DW) images acquired with different b-values, often suffers from low SNR, which can introduce large variance in ADC maps. Unfortunately, there is no consensus on the optimal b-values to maximize the noise performance of ADC map. In this work, we determine the optimal b-values to maximize the noise performance of ADC mapping by using a Cram{\'e}r-Rao Lower Bound (CRLB) approach under realistic noise assumptions. The strong agreement between the CRLB-based analysis, Monte-Carlo simulations, and ADC phantom experiment, suggests the utility of this approach to optimize DW-MRI acquisitions.

}, author = {{\'O}scar Pe{\~n}a-Nogales and Diego Hernando and Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a} } @conference {689, title = {Effect of sampling on the estimation of the apparent coefficient of diffusion in MRI}, booktitle = {ICASSP 2017}, year = {2017}, month = {2017}, publisher = {IEEE signal processing Society}, organization = {IEEE signal processing Society}, address = {New Orleans, LA}, author = {Santiago Aja-Fern{\'a}ndez and {\'O}scar Pe{\~n}a-Nogales and Rodrigo de Luis-Garc{\'\i}a} } @conference {700, title = {Groupwise Non-Rigid Registration on Multiparametric Abdominal DWI Acquisitions for Robust ADC Estimation: Comparison with Pairwise Approaches and Different Multimodal Metrics}, booktitle = {International Symposium on Biomedical Imaging: From Nano to Macro (ISBI2017)}, year = {2017}, month = {2017}, address = {Melbourne, Australia}, abstract = {

Registration of diffusion weighted datasets remains a challenging\ task in the process of quantifying diffusion indexes.\ Respiratory and cardiac motion, as well as echo-planar characteristic\ geometric distortions, may greatly limit accuracy on\ parameter estimation, specially for the liver. This work proposes\ a methodology for the non-rigid registration of multiparametric\ abdominal diffusion weighted imaging by using\ different well-known metrics under the groupwise paradigm.\ A three-stage validation of the methodology is carried out on\ a computational diffusion phantom, a watery solution phantom\ and a set of voluntary patients. Diffusion estimation\ accuracy has been directly calculated on the computational\ phantom and indirectly by means of a residual analysis on\ the real data. On the other hand, effectiveness in distortion\ correction has been measured on the phantom. Results have\ shown statistical significant improvements compared to pairwise\ registration being able to cope with elastic deformations.

}, author = {Santiago Sanz-Est{\'e}banez and {\'O}scar Pe{\~n}a-Nogales and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {743, title = {Libstable: Fast, parallel, and high-precision computation of α-stable distributions in R, C/C++, and MATLAB}, journal = {Journal of Statistical Software}, volume = {78}, year = {2017}, pages = {1-25}, doi = {10.18637/jss.v078.i01}, author = {J Royuela-del-Val and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @article {773, title = {Matching pursuit-based compressive sensing in a wearable biomedical accelerometer fall diagnosis device}, journal = {Biomedical signal processing and control}, volume = {33}, year = {2017}, pages = {96{\textendash}108}, author = {Gibson, Ryan M and Amira, Abbes and Ramzan, Naeem and Pablo Casaseca-de-la-Higuera and Pervez, Zeeshan} } @proceedings {725, title = {Monte-Carlo Analysis of Quantitative Diffusion Measurements Using Motion-Compensated Diffusion Weighting Waveforms}, year = {2017}, pages = {1733}, address = {Honolulu, HI, USA}, abstract = {

Advanced diffusion MRI acquisition strategies based on motion-compensated diffusion-econding waveforms have been proposed to reduce the signal voids caused by tissue motion. However, quantitative diffusion measurements obtained from these motion-compensated waveforms may be baised relative to standard monopolar gradient waveforms. This study evaluated the effect of different diffusion encoding gradient waveforms on the signal decay and diffusion measurements, using Monte-Carlo simulations with different microstructures and several reconstruction signal models. The results show substantial bias in observed signal decay and quantiative diffusion measurements in the same microstructure across different gradient waveforms, in the presence of restricted diffusion.

}, author = {Yuxin Zhang and {\'O}scar Pe{\~n}a-Nogales and James H. Holmes and Diego Hernando} } @article {666, title = {Non-Stationary Rician Noise Estimation in Parallel MRI using a Single Image: a Variance-Stabilizing Approach}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {39}, year = {2017}, month = {2017}, pages = {2015-2029}, chapter = {2015}, abstract = {

Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e. it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data. Besides, some methods show an undesirable granular pattern on the estimates as a side effect of local estimation. Finally, some methods make strong assumptions that just hold in the case of high signal-to-noise ratio (SNR), which limits their usability in real scenarios. We propose a new automatic noise estimation technique for non-stationary Rician noise that overcomes the aforementioned drawbacks. Its effectiveness is due to the derivation of a variance-stabilizing transformation designed to deal with any SNR. The method was compared to the main state-of-the-art methods in synthetic and real scenarios. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.

}, issn = {0162-8828}, doi = {10.1109/TPAMI.2016.2625789}, author = {Tomasz Pieciak and Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas S{\'a}nchez-Ferrero} } @conference {871, title = {Non-intrusive image processing Thompson orange grading methods}, booktitle = {2017 56th FITCE Congress}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, abstract = {A key issue in fruit export is classification and sorting for marketing. In this work image processing techniques are used to grad Thompson orange fruit. For this purpose, fourteen parameters were extracted, comprising area, eccentricity, perimeter, length/area, blue value, green value, red value, width, contrast, texture, width/area, width/length, roughness, and length. Adaptive neuro fuzzy inference system (ANFIS), linear, and nonlinear regression methods were used. Based on results, mean square error (MSB), sum squared error (SSE) and coefficient of determination (R 2 ) were 3.47e-08, 3.47e-07, 0.988 (ANFIS), 51.33, 4927.59, 0.866 (linear reg.) and 64.85, 6092.5, 0.832 (non-linear reg.), respectively. ANFIS model was shown as the best fit model based on previously listed performance evaluation criteria.}, doi = {https://doi.org/10.1109/FITCE.2017.8093004}, url = {https://ieeexplore.ieee.org/abstract/document/8093004}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @proceedings {724, title = {Optimal design of motion-compensated diffusion gradient waveforms }, year = {2017}, pages = {3340}, address = {Honolulu, HI, USA}, abstract = {

Diffusion-Weighted MRI (DW-MRI) often suffers from motion-related artifacts in organs that experience physiological motion. Importantly, organ motion during the application of diffusion gradients results in signal losses, which complicate image interpretation and bias quantitative measures. Motion-compensated gradient designs have been proposed, however they typically result in substantially lower b-values or severe concomitant gradient effects. In this work, we develop an approach for design of first- and second-order motion-compensated gradient waveforms based on a b-value maximization formulation including concomitant gradient nulling, and we compare it to existing techniques. The proposed design provides optimized b-values with motion compensation and concomitant gradient nulling.

}, author = {{\'O}scar Pe{\~n}a-Nogales and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Yuxin Zhang and James H. Holmes and Diego Hernando} } @article {873, title = {A blood orange computer vision sorting system}, year = {2017}, abstract = {To have a proper sorting system with a low error rate can be very useful in automatic packaging of products. Furthermore, physical dimensions and shape are important in sorting and sizing of fruits and vegetables. In this paper Iranian orange (blood orange) are considered to present an automatic mass sorting system with low error rate using image processing coupled with an adaptive neurofuzzy inference system (ANFIS). Linear regression analysis was used to compare results and an efficient algorithm was designed and implemented in MatLab. This algorithm is able to measure area, eccentricity, perimeter, length/area, red, green, and blue RGB components, width, contrast, texture, width/area, width/length, roughness and length. In ANFIS model, samples were divided into two sets: 70\% for training and 30\% for testing. Best ANFIS, linear and nonlinear regression models, yielded values of the coefficient of determination (R2), sum squared error (SSE), and mean squared error (MSE) of 0.989, 21.46, 1.65 (ANFIS), 0.91, 1156.69, 12.05 (linear) and 0.88, 1538.10, 15.86 (nonlinear), respectively. Based on results, ANFIS model showed clearly better capability for mass prediction compared to both linear and nonlinear regression. A prototype for an automatic non-intrusive orange mass sorting system is depicted to conclude.}, doi = {https://doi.org/10.1049/cp.2017.0167}, url = {https://digital-library.theiet.org/content/conferences/10.1049/cp.2017.0167}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @conference {872, title = {A new method based on computer vision for non-intrusive orange peel sorting}, booktitle = {2017 56th FITCE Congress}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, abstract = {As it is well-known, orange peel is used for making jam and oil. For this purpose, orange samples with high peel thickness are best. In order to predict peel thickness in orange fruit, we present a system based in image features, comprising: area, eccentricity, perimeter, length/area, blue value, green value, red value, wide, contrast, texture, wide/area, wide/length, roughness, and length. A novel identification solution based on the hybrid of particle swarm optimization (PSO), genetic algorithm (GA) and artificial neural network (ANN) is proposed. In addition, principal component analysis (PCA) has been applied to reduce the number of dimensions, without much loss of information. Taguchi{\textquoteright}s robust optimization technique has been applied to determine the optimal setting for parameters of PSO, GA, and ANN. The optimal level of factors were: Number of Neuron in first layer=7, Number of Neuron in second layer=2, Maximum Iteration=400, Crossover probability=0.7, Mutation probability=0.1, and Swarm (Population) Size=200. Results for prediction of orange peel thickness based on levels that are achieved by Taguchi method were evaluated by five performance measures: the coefficient of determination (R 2 ), mean squared error (MSE), mean absolute error (MAE), sum square error (SSE), and root mean square error (RMSE), reaching values of 0.8571, 0.0123, 0.0924, 1.392, and 0.1109, respectively.}, doi = {https://doi.org/10.1109/FITCE.2017.8093001}, url = {https://ieeexplore.ieee.org/abstract/document/8093001}, author = {Sabzi, Sajad and Yousef Abbaspour-Gilandeh and J I Arribas} } @conference {600, title = {An Automated Tensorial Classification Procedure for Left Ventricular Hypertrophic Cardiomyopathy}, booktitle = {IWBBIO 2016 (4th International Work-Conference on Bioinformatics and Biomedical Engineering)}, volume = {1}, year = {2016}, month = {2016}, pages = {1-12}, edition = {LNBI 9656}, address = {Granada, Spain}, abstract = {

Cardiovascular diseases are the leading cause of death globally. Therefore, classi cation tools play a major role in prevention and\ treatment of these diseases. Statistical learning theory applied to magnetic resonance imaging has led to the diagnosis of a variety of cardiomyopathies states.\ We propose a two-stage classi cation scheme capable of\ distinguishing between heterogeneous groups of hypertrophic cardiomyopathies and healthy patients.\ A multimodal processing pipeline is employed to estimate robust tensorial descriptors of myocardial mechanical\ properties for both short-axis and long-axis magnetic resonance tagged\ images using the least absolute deviation method. A homomorphic ltering procedure is used to align the cine segmentations to the tagged sequence and provides 3D tensor information in meaningful areas.\ Results\ have shown that the proposed pipeline provides tensorial measurements\ on which classi ers for the study of hypertrophic cardiomyopathies can\ be built with acceptable performance even for reduced samples sets.

}, keywords = {Fuzzy clustering, HARmonic Phase, Homomorphic Filtering, Hypertrophic Cardiomyopathy, Least Absolute Deviation, Magnetic Resonance Tagging, Support Vector Machines}, doi = {10.1007/978-3-319-31744-1 17}, author = {Santiago Sanz-Est{\'e}banez and J Royuela-del-Val and S. Merino-Caviedes and A. Revilla-Orodea and T. Sevilla-Ruiz and Martin-Fernandez, M and Carlos Alberola-Lopez} } @conference {663, title = {Cardio-respiratory motion estimation for compressed sensing reconstruction of free-breathing 2D cine MRI}, booktitle = {Modulated/Incomplete Data 2016, SFB Workshop.}, year = {2016}, month = {2016}, publisher = {Mathematical Optimization and Applications in Biomedical Sciences (MOBIS), SFB Research Center}, organization = {Mathematical Optimization and Applications in Biomedical Sciences (MOBIS), SFB Research Center}, address = {Graz, Austria}, abstract = {

Respiratory motion is still an issue in MRI of the heart despite the introduction of Compressed Sensing (CS) techniques, which significantly accelerate acquisition [1]. Recently [2], a double-binning scheme was introduced in which k-space data is split according both to the cardiac and respiratory phases (Fig. 1); at reconstruction, sparsity along both dimensions is exploited. Other methods introduce motion estimation and compensation in CS (MC-CS) either to correct the respiratory motion [3] or to promote sparsity for reconstruction improvement [4]. In this work, we propose a technique to jointly estimate the respiratory and cardiac motions within a double-binning scheme, enabling the MC-CS reconstruction of respiratory resolved free-breathing 2D CINE MRI. Preliminary results on synthetic, highly undersampled (x16) Cartesian setup are shown.

[1] Lustig et al. MRM 2007, [2] Feng et al. MRM 2015, [3] Usman et al. MRM 2013. [4]\ Royuela-del-Val et al. MRM 2015.

}, author = {J Royuela-del-Val and Marcos Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @conference {775, title = {Effect of importance sampling on robust segmentation of audio-cough events in noisy environments}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the}, year = {2016}, publisher = {IEEE}, organization = {IEEE}, author = {Monge-Alvarez, Jes{\'u}s and Hoyos-Barcel{\'o}, Carlos and Lesso, Paul and Escudero, Javier and Dahal, Keshav and Pablo Casaseca-de-la-Higuera} } @conference {687, title = {Harmonic Auto-Regularization for Non Rigid Groupwise Registration in Cardiac Magnetic Resonance Imaging.}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica 2016}, year = {2016}, month = {11/2016}, address = {Valencia, Spain}, abstract = {

In this paper we present a new approach for non rigid groupwise registration of cardiac magnetic resonance images by means of free-form deformations, imposing a prior harmonic deformation assumption. The procedure proposes a primal-dual framework for solving an equality constrained minimization problem, which allows an automatic estimate of the trade-off between image fidelity and the Laplacian smoothness terms for each iteration. The method has been applied to both a 4D extended cardio-torso phantom and to a set of voluntary patients. The accuracy of the method has been measured for the synthetic experiment as the difference in modulus between the estimated displacement field and the ground truth; as for the real data, we have calculated the Dice coefficient between the contour manual delineations provided by two cardiologists at end systolic phase and those provided by them at end diastolic phase and, consequently propagated by the registration algorithm to the systolic instant. The automatic procedure turns out to be competitive in motion compensation with other methods even though their parameters have been previously set for optimal performance in different scenarios.

}, author = {Santiago Sanz-Est{\'e}banez and J Royuela-del-Val and T. Sevilla-Ruiz and Revilla-Orodea, A. and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {616, title = {Influence of ultrasound speckle tracking strategies for motion and strain estimation}, journal = {Medical Image Analysis}, volume = {32}, year = {2016}, month = {2016}, pages = {184 - 200}, abstract = {

Abstract Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system.

}, issn = {1361-8415}, doi = {http://dx.doi.org/10.1016/j.media.2016.04.002}, url = {http://www.sciencedirect.com/science/article/pii/S1361841516300202}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {602, title = {Jacobian weighted temporal total variation for motion compensated compressed sensing reconstruction of dynamic MRI}, journal = {Magnetic Resonance in Medicine}, year = {2016}, month = {2016}, abstract = {

Purpose:\ To eliminate the need of spatial intraframe regularization in a recently reported dynamic MRI compressed-sensing-based reconstruction method with motion compensation and to increase its performance.

Theory and Methods: We propose a new regularization metric based on the introduction of a spatial weighting measure given by the Jacobian of the estimated deformations. It shows convenient discretization properties and, as a byproduct, it also provides a theoretical support to a result reported by others based on an intuitive design. The method has been applied to the reconstruction of both short and long axis views of the heart of four healthy volunteers. Quantitative image quality metrics as well as straightforward visual assessment are reported.

Results: Short and long axis reconstructions of cardiac cine MRI sequences have shown superior results than previously reported methods both in terms of quantitative metrics and of visual assessment. Fine details are better preserved due to the lack of additional intraframe regularization, with no significant image artifacts even for an acceleration factor of 12.

Conclusions: The proposed Jacobian Weighted temporal Total Variation results in better reconstructions of highly undersampled cardiac cine MRI than previously proposed methods and sets a theoretical ground for forward and backward predictors used elsewhere.

}, keywords = {compressed sensing, dynamic MRI reconstruction, group-wise registration, motion estimation}, doi = {10.1002/mrm.26198}, url = {http://onlinelibrary.wiley.com/doi/10.1002/mrm.26198}, author = {J Royuela-del-Val and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @article {597, title = {Multi-oriented windowed harmonic phase reconstruction for robust cardiac strain imaging}, journal = {Medical Image Analysis}, volume = {29}, year = {2016}, month = {2016}, pages = {1-11}, chapter = {1}, author = {Lucilio Cordero-Grande and J Royuela-del-Val and Santiago Sanz-Est{\'e}banez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {776, title = {Multiple comparator classifier framework for accelerometer-based fall detection and diagnostic}, journal = {Applied Soft Computing}, volume = {39}, year = {2016}, pages = {94{\textendash}103}, author = {Gibson, Ryan M and Amira, Abbes and Ramzan, Naeem and Pablo Casaseca-de-la-Higuera and Pervez, Zeeshan} } @conference {603, title = {Multiresolution Reconstruction of Real-Time MRI with Motion Compensated Compressed Sensing: Application to 2D Free-Breathing Cardiac MRI}, booktitle = {International Symposium on Biomedical Engineering: From Nano to Macro}, year = {2016}, month = {2016}, publisher = {IEEE Signal Processing Society}, organization = {IEEE Signal Processing Society}, address = {Prague, Check Republic}, abstract = {

Real-time MRI is a novel noninvasive imaging technique that allows the visualization of physiological processes with both good spatial and temporal resolutions. However, the reconstruction of images from highly undersampled data, needed to perform real-time imaging, remains challenging. Recently, the combination of Compressed Sensing theory with motion compensation techniques has shown to achieve better results than previous methods. In this work we describe a real-time MRI algorithm based on the acquisition of the k-space data following a Golden Radial trajectory, Compressed Sensing reconstruction and a groupwise temporal registration algorithm for the estimation and compensation of the motion in the image, all this embedded within a temporal multiresolution scheme. We have applied the proposed method to the reconstruction of free-breathing acquisition of short axis views of the heart, achieving a temporal resolution of 25ms, corresponding to an acceleration factor of 28 with respect to fully sampled Cartesian acquisitions.

}, keywords = {Compressive sensing \& sampling, Image reconstruction {\textendash} analytical \& iterative methods, Magnetic resonance imaging (MRI)}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and M. Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @conference {615, title = {Spatial and Spectral Anisotropy in HARP Images: An Automated Approach}, booktitle = {International Symposium on Biomedical Imaging: From Nano to Macro (ISBI2016)}, year = {2016}, month = {2016}, address = {Prague, Czech Republic}, abstract = {

Strain and related tensors play a major role in cardiac function\ characterization, so correct estimation of the local phase\ in tagged images is crucial for quantitative myocardial motion\ studies. We propose an Harmonic Phase related procedure\ that is adaptive in the spatial and the spectral domains: as for\ the former, we use an angled-steered analysis window prior to\ the Fourier Transform; as for the latter, the bandpass filter is\ also angle-adaptive. Both of them are narrow in the modulation\ direction and wide in the orthogonal direction.

Moreover,\ no parameters are manually set since their values are partially\ based on the information available at the DICOM headers and\ additional information is estimated from data. The procedure
is tested in terms of accuracy (on synthetic data) and reproducibility\ (on real data) of the deformation gradient tensor,\ measured by means of the distribution of the Frobenius norm\ differences between two tensor datasets.

}, keywords = {Anisotropic Gaussian Window, Automatic Band-Pass Filtering, HARmonic Phase, Strain Tensor, Tagged Magnetic Resonance Imaging, Thresholding}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {654, title = {Spatially-variant noise filtering in Magnetic Resonance Imaging: A Consensus-based approach}, journal = {Knowledge-Based Systems}, year = {2016}, month = {2016}, doi = {http://dx.doi.org/10.1016/j.knosys.2016.05.053}, url = {http://www.sciencedirect.com/science/article/pii/S0950705116301575}, author = {Luis Gonz{\'a}lez-Jaime and Gonzalo Vegas-S{\'a}nchez-Ferrero and Etienne E. Kerre and Santiago Aja-Fern{\'a}ndez} } @book {660, title = {Statistical Analysis of Noise in MRI. Modeling, Filtering and Estimation}, year = {2016}, pages = {327}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Switzerland}, abstract = {

This unique text presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques. Features: provides a complete framework for the modeling and analysis of noise in MRI, considering different modalities and acquisition techniques; describes noise and signal estimation for MRI from a statistical signal processing perspective; surveys the different methods to remove noise in MRI acquisitions from a practical point of view; reviews different techniques for estimating noise from MRI data in single- and multiple-coil systems for fully sampled acquisitions; examines the issue of noise estimation when accelerated acquisitions are considered, and parallel imaging methods are used to reconstruct the signal; includes appendices covering probability density functions, combinations of random variables used to derive estimators, and useful MRI datasets.

}, issn = {978-3-319-39933-1}, doi = {http://dx.doi.org/10.1007/978-3-319-39934-8}, url = {http://link.springer.com/book/10.1007/978-3-319-39934-8}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @conference {774, title = {Systematic infrared image quality improvement using deep learning based techniques}, booktitle = {Remote Sensing Technologies and Applications in Urban Environments}, year = {2016}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Zhang, Huaizhong and Pablo Casaseca-de-la-Higuera and Luo, Chunbo and Wang, Qi and Kitchin, Matthew and Parmley, Andrew and Monge-Alvarez, Jesus} } @article {SanJos{\'e}Revuelta2016561, title = {Three Natural Computation methods for joint channel estimation and symbol detection in multiuser communications}, journal = {Applied Soft Computing}, volume = {49}, year = {2016}, pages = {561 - 569}, abstract = {Abstract This paper studies three of the most important optimization algorithms belonging to Natural Computation (NC): genetic algorithm (GA), tabu search (TS) and simulated quenching (SQ). A concise overview of these methods, including their fundamentals, drawbacks and comparison, is described in the first half of the paper. Our work is particularized and focused on a specific application: joint channel estimation and symbol detection in a Direct-Sequence/Code-Division Multiple-Access (DS/CDMA) multiuser communications scenario; therefore, its channel model is described and the three methods are explained and particularized for solving this. Important issues such as suboptimal convergence, cycling search or control of the population diversity have deserved special attention. Several numerical simulations analyze the performance of these three methods, showing, as well, comparative results with well-known classical algorithms such as the Minimum Mean Square Error estimator (MMSE), the Matched Filter (MF) or Radial Basis Function (RBF)-based detection schemes. As a consequence, the three proposed methods would allow transmission at higher data rates over channels under more severe fading and interference conditions. Simulations show that our proposals require less computational load in most cases. For instance, the proposed \{GA\} saves about 73\% of time with respect to the standard GA. Besides, when the number of active users doubles from 10 to 20, the complexity of the proposed \{GA\} increases by a factor of 8.33, in contrast to 32 for the optimum maximum likelihood detector. The load of \{TS\} and \{SQ\} is around 15{\textendash}25\% higher than that of the proposed GA.}, keywords = {Population diversity}, issn = {1568-4946}, doi = {http://dx.doi.org/10.1016/j.asoc.2016.08.034}, url = {http://www.sciencedirect.com/science/article/pii/S1568494616304288}, author = {Luis M. San-Jos{\'e}-Revuelta and J I Arribas} } @conference {655, title = {Variance Stabilization of Noncentral-Chi Data: Application to Noise Estimation in MRI}, booktitle = {2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, 2016}, year = {2016}, month = {2016}, address = {Prague, Czech Republic}, author = {Tomasz Pieciak and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @conference {690, title = {Whole-heart single breath-hold cardiac cine: A robust motion-compensated compressed sensing reconstruction method}, booktitle = {International Workshop on Reconstruction and Analysis of Moving Body Organs (RAMBO/MICCAI) }, year = {2016}, month = {2016}, address = {Athens, Greece}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Marcos Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @article {7460246, title = {A computer-aided diagnosis system with EEG based on the P3b wave during an auditory odd-ball task in schizophrenia}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {PP}, number = {99}, year = {2016}, pages = {1-1}, abstract = {Objective: To design a Computer-aided diagnosis (CAD) system using an optimized methodology over the P3b wave in order to objectively and accurately discriminate between healthy controls (HC) and schizophrenic subjects (SZ). Methods: We train, test, analyze, and compare various machine learning classification approaches optimized in terms of the correct classification rate (CCR), the degenerated Youden{\textquoteright}s index (DYI) and the area under the receiver operating curve (AUC). CAD system comprises five stages: electroencephalography (EEG) preprocessing, feature extraction, seven electrode groupings, discriminant feature selection, and binary classification. Results: With two optimal combinations of electrode grouping, filtering, feature selection algorithm, and classification machine, we get either a mean CCR = 93.42\%, specificity = 0.9673, sensitivity = 0.8727, DYI = 0.9188, and AUC = 0.9567 (total-15 Hz-J5-MLP), or a mean CCR = 92.23\%, specificity = 0.9499, sensitivity = 0.8838, DYI = 0.9162, and AUC = 0.9807 (right hemisphere-35 Hz-J5-SVM), which to our knowledge are higher than those available to date. Conclusions: We have verified that a more restrictive low-pass filtering achieves higher CCR as compared to others at higher frequencies in the P3b wave. In addition, results validate previous hypothesis about the importance of the parietal-temporal region, associated with memory processing, allowing us to identify powerful {feature,electrode} pairs in the diagnosis of schizophrenia, achieving higher CCR and AUC in classification of both right and left Hemispheres, and parietal-temporal EEG signals, like, for instance, the {PSE, P4} pair (J5 and mutual information feature selection). Significance: Diagnosis of schizophrenia is made thoroughly by psychiatrists but as any human-based decision that has a subjective component. This CAD system provides the human expert with an objective complimentary measure to help him in diagnosing schizophrenia.}, keywords = {Computer aided diagnosis, Design automation, Electrodes, Electroencephalography, Feature extraction, Indexes, Sensitivity}, issn = {0018-9294}, doi = {10.1109/TBME.2016.2558824}, url = {https://ieeexplore.ieee.org/abstract/document/7460246}, author = {L. Santos-Mayo and Luis Miguel San-Jose-Revuelta and J I Arribas} } @article {627, title = {Adjugate Diffusion Tensors for Geodesic Tractography in White Matter}, journal = {Journal of Mathematical Imaging and Vision}, volume = {54}, year = {2015}, pages = {1{\textendash}14}, abstract = {

One of the approaches in diffusion tensor imaging is to consider a Riemannian metric given by the inverse diffusion tensor. Such a metric is used for geodesic tractography and connectivity analysis in white matter. We propose a metric tensor given by the adjugate rather than the previously proposed inverse diffusion tensor. The adjugate metric can also be employed in the sharpening framework. Tractography experiments on synthetic and real brain diffusion data show improvement for high-curvature tracts and in the vicinity of isotropic diffusion regions relative to most results for inverse (sharpened) diffusion tensors, and especially on real data. In addition, adjugate tensors are shown to be more robust to noise.

}, issn = {1573-7683}, doi = {10.1007/s10851-015-0586-8}, url = {http://dx.doi.org/10.1007/s10851-015-0586-8}, author = {Andrea Fuster and Tom Dela-Haije and Antonio Trist{\'a}n-Vega and Birgit Plantinga and Carl-Fredik Westin and Luc Florack} } @article {448, title = {Anisotropic Diffusion Filter with Memory based on Speckle Statistics for Ultrasound Images}, journal = {IEEE Transactions on image processing}, volume = {24}, year = {2015}, chapter = {345}, doi = {http://dx.doi.org/10.1109/TIP.2014.2371244}, author = {Gabriel Ramos-Llorden and Gonzalo Vegas-S{\'a}nchez-Ferrero and Marcos Martin-Fernandez and Carlos Alberola-Lopez and Santiago Aja-Fern{\'a}ndez} } @article {de2014attention, title = {Attention Deficit/Hyperactivity Disorder and Medication with Stimulants in Young Children: A DTI Study}, journal = {Progress in Neuro-Psychopharmacology and Biological Psychiatry}, volume = {57}, year = {2015}, publisher = {Elsevier}, chapter = {176}, doi = {http://dx.doi.org/10.1016/j.pnpbp.2014.10.014}, author = {Rodrigo de Luis-Garc{\'\i}a and Cab{\'u}s-Pi{\~n}ol, Gemma and Imaz-Roncero, Carlos and Daniel Argibay-Qui{\~n}ones and Gonzalo Barrio-Arranz and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @proceedings {543, title = {Blind Estimation of Spatially Variant Noise in GRAPPA MRI}, year = {2015}, pages = {SuAT7.4}, abstract = {

The reconstruction process in multiple coil MRI scanners makes the noise features in the final magnitude image become non-stationary, i.e. the variance of noise becomes position-dependent. Therefore, most noise estimators proposed in the literature cannot be used in multiple-coil acquisitions. This effect is augmented when parallel imaging methods, such as GRAPPA, are used to increase the acquisition rate.

In this work we propose a new technique that allows the estimation of the spatially variant maps of noise from the GRAPPA reconstructed signal when only one single image is available and no additional information is provided. Other estimators in the literature need extra information that is not always available, which has supposed an important limitation in the usage of noise models for GRAPPA. The proposed approach uses a homomorphic separation of the spatially variant noise in two terms: a stationary noise term and one low frequency signal that correspond to the x-dependent variance of noise. The non-stationary variance of noise is estimated by a low pass filtering. The noise term is obtained via prior wavelet decomposition. Results in real and synthetic experiments evidence the suitability of the simplification used and the good performance of the proposed methodology.

}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @conference {598, title = {Cardiac Strain Assessment for Fibrotic Myocardial Tissue Detection in Left Ventricular Hypertrophic Cardiomyopathy}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica.}, year = {2015}, month = {2015}, address = {Madrid, Spain.}, abstract = {

This work proposes an image processing methodology to\ distinguish fibrotic from normal tissue by the assessment of the\ local mechanical properties of the myocardium in magnetic\ resonance tagging images. The procedure uses the information\ provided by short axis images of the above mentioned modality\ to estimate the Green-Lagrange strain tensor; a modified\ method based on the Harmonic Phase is employed for motion\ estimation. The method has been applied to the analysis of the\ local deformation patterns in a set of patients affected by\ hypertrophic cardiomyopathy in order to find the agreement\ between hyperenhanced zones in late enhancement images and\ areas in the myocardium with abnormal tensor values (both the\ radial and the circumferential components as well as the\ shearing component have been accounted for). The agreement is\ measured taken as ground truth manual segmentation of late\ enhancement images carried out by two cardiologists. Finally, a\ set of example images illustrate the agreement between both\ techniques.

}, author = {Santiago Sanz-Est{\'e}banez and S. Merino-Caviedes and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @proceedings {574, title = {Effect of Downsampling and Compressive Sensing on Audio-based Continuous Cough Monitoring}, volume = {37}, year = {2015}, pages = {6231-6235}, address = {Milan, Italy}, author = {Pablo Casaseca-de-la-Higuera and Lesso, Paul and Mckinstry, Brian and Pinnock, Hilary and Rabinovich, Roberto and McCloughan, Lucy and Monge-{\'A}lvarez, Jes{\'u}s} } @article {628, title = {Efficient and Robust Image Restoration Using Multiple-Feature L2-Relaxed Sparse Analysis Priors}, journal = {IEEE Transactions on Image Processing}, volume = {24}, year = {2015}, month = {Dec}, pages = {5046-5059}, abstract = {

We propose a novel formulation for relaxed analysis-based sparsity in multiple dictionaries as a general type of prior for images, and apply it for Bayesian estimation in image restoration problems. Our formulation of a l2 -relaxed l0 pseudo-norm prior allows for an especially simple maximum a posteriori estimation iterative marginal optimization algorithm, whose convergence we prove. We achieve a significant speedup over the direct (static) solution by using dynamically evolving parameters through the estimation loop. As an added heuristic twist, we fix in advance the number of iterations, and then empirically optimize the involved parameters according to two performance benchmarks. The resulting constrained dynamic method is not just fast and effective, it is also highly robust and flexible. First, it is able to provide an outstanding tradeoff between computational load and performance, in visual and objective, mean square error and structural similarity terms, for a large variety of degradation tests, using the same set of parameter values for all tests. Second, the performance benchmark can be easily adapted to specific types of degradation, image classes, and even performance criteria. Third, it allows for using simultaneously several dictionaries with complementary features. This unique combination makes ours a highly practical deconvolution method.

}, keywords = {Bayes methods, Bayesian estimation, Convergence, Dictionaries, Estimation, Kernel, L2-relaxed L0 pseudo norm, L2-relaxed L0 pseudo-norm prior, L2-relaxed sparse analysis priors, Maximum likelihood estimation, Optimization, Redundancy, computational load, constrained dynamic method, deconvolution, deconvolution method, dynamically evolving parameters, estimation loop, fast constrained dynamic algorithm, image restoration, iterative marginal optimization, iterative methods, maximum a posteriori estimation, mean square error, mean square error methods, multiple representations, multiple-feature L2-relaxed sparse analysis priors, optimisation, robust tunable parameters, structural similarity terms}, issn = {1057-7149}, doi = {10.1109/TIP.2015.2478405}, author = {Javier Portilla and Antonio Trist{\'a}n-Vega and Ivan W. Selesnick} } @article {431, title = {Fast calculation of alpha-stable density functions based on off-line precomputations. Application to ML parameter estimation}, journal = {Digital Signal Processing}, volume = {38}, year = {2015}, pages = {1-12}, chapter = {1}, keywords = {Delaunay triangulation, Interpolation, Parameter estimation, alpha-Stable}, doi = {10.1016/j.dsp.2014.12.009}, author = {Federico Simmross-Wattenberg and Marcos Mart{\'\i}n-Fern{\'a}ndez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @article {567, title = {Impact of MR Acquisition Parameters on DTI Scalar Indexes: A Tractography Based Approach}, journal = {PLoS ONE}, volume = {10}, year = {2015}, pages = {e0137905}, doi = {10.1371/journal.pone.0137905}, url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0137905}, author = {Gonzalo Barrio-Arranz and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Marcos Mart{\'\i}n-Fern{\'a}ndez and Santiago Aja-Fern{\'a}ndez} } @article {532, title = {Improving GRAPPA reconstruction by frequency discrimination in the ACS lines}, journal = {International Journal of Computer Assisted Radiology and Surgery}, volume = {10}, year = {2015}, month = {2015}, pages = {1699-1710}, chapter = {1699}, abstract = {
Purpose
GRAPPA is a well-known parallel imaging method that recovers the MR magnitude image from aliasing by using a weighted interpolation of the data in k-space. To estimate the optimal reconstruction weights, GRAPPA uses a band along the center of the k-space where the signal is sampled at the Nyquist rate, the so-called autocalibrated (ACS) lines. However, while the subsampled lines usually belong to the medium- to high-frequency areas of the spectrum, the ACS lines include the low-frequency areas around the DC component. The use for estimation and reconstruction of areas of the k-space with very different features may negatively affect the final reconstruction quality. We propose a simple, yet powerful method to eliminate reconstruction artifacts, based on the discrimination of the low-frequency spectrum.
Methods
The proposal to improve the estimation of the weights lays on a proper selection of the coefficients within the ACS lines, which advises discarding those points around the DC component. A simple approach is the elimination of a square window in the center of the k-space, although more developed approaches can be used.
Results
The method is tested using real multiple-coil MRI acquisitions. We empirically show this approach achieves great enhancement rates, while keeping the same complexity of the original GRAPPA and reducing the g-factor. The reconstruction is even more accurate when combined with other reconstruction methods. Improvement rates of 35\ \% are achieved for 32 ACS and acceleration rate of 3.
Conclusions
The method proposed highly improves the accuracy of the GRAPPA coefficients and therefore the final image reconstruction. The method is fully compatible with the original GRAPPA formulation and with other optimization methods proposed in literature, and it can be easily implemented into the commercial scanning software.
}, doi = {10.1007/s11548-015-1172-7}, author = {Santiago Aja-Fern{\'a}ndez and Daniel Garc{\'\i}a-Mart{\'\i}n and Antonio Trist{\'a}n-Vega and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @article {541, title = {A Maximum Likelihood Approach to Diffeomorphic Speckle Tracking for 3D Strain Estimation in Echocardiography}, journal = {Medical Image Analysis}, year = {2015}, pages = {-}, abstract = {

Abstract The strain and strain-rate measures are commonly used for the analysis and assessment of regional myocardial function. In echocardiography (EC), the strain analysis became possible using Tissue Doppler Imaging (TDI). Unfortunately, this modality shows an important limitation: the angle between the myocardial movement and the ultrasound beam should be small to provide reliable measures. This constraint makes it difficult to provide strain measures of the entire myocardium. Alternative non-Doppler techniques such as Speckle Tracking (ST) can provide strain measures without angle constraints. However, the spatial resolution and noisy appearance of speckle still make the strain estimation a challenging task in EC. Several maximum likelihood approaches have been proposed to statistically characterize the behavior of speckle, which results in a better performance of speckle tracking. However, those models do not consider common transformations to achieve the final B-mode image (e.g. interpolation). This paper proposes a new maximum likelihood approach for speckle tracking which effectively characterizes speckle of the final B-mode image. Its formulation provides a diffeomorphic scheme than can be efficiently optimized with a second-order method. The novelty of the method is threefold: First, the statistical characterization of speckle generalizes conventional speckle models (Rayleigh, Nakagami and Gamma) to a more versatile model for real data. Second, the formulation includes local correlation to increase the efficiency of frame-to-frame speckle tracking. Third, a probabilistic myocardial tissue characterization is used to automatically identify more reliable myocardial motions. The accuracy and agreement assessment was evaluated in a set of 16 synthetic image sequences for three different scenarios: normal, acute ischemia and acute dyssynchrony. The proposed method was compared to six speckle tracking methods. Results revealed that the proposed method is the most accurate method to measure the motion and strain with an average median motion error of 0.42\ mm and a median strain error of 2.0 {\textpm} 0.9\%, 2.1 {\textpm} 1.3\% and 7.1 {\textpm} 4.9\% for circumferential, longitudinal and radial strain respectively. It also showed its capability to identify abnormal segments with reduced cardiac function and timing differences for the dyssynchrony cases. These results indicate that the proposed diffeomorphic speckle tracking method provides robust and accurate motion and strain estimation.

}, doi = {http://dx.doi.org/10.1016/j.media.2015.05.001}, url = {http://www.sciencedirect.com/science/article/pii/S1361841515000687}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Johan G. Bosch and Santiago Aja-Fern{\'a}ndez} } @article {573, title = {Multiple Comparator Classifier Framework for Accelerometer-Based Fall Detection and Diagnostic}, journal = {Applied Soft Computing}, year = {2015}, month = {In press}, author = {Gibson, Ryan M and Amira, Abbes and Ramzan, Naeem and Pablo Casaseca-de-la-Higuera and Pervez, Zeeshan} } @conference {588, title = {Multiresolution Reconstruction of Real-Time MRI with Motion Compensated Compressed Sensing: Application to 2D Free-Breathing Cardiac MRI}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2015}, month = {11/2015}, address = {Madrid}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Marcos Martin-Fernandez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @article {533, title = {Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruction of Breath-Hold Cardiac Cine MRI}, journal = {Magnetic Resonance in Medicine}, year = {2015}, doi = {10.1002/mrm.25733}, author = {J Royuela-del-Val and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-Lopez} } @inbook {572, title = {PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones}, booktitle = {Lecture Notes in Computer Science}, volume = {9117}, year = {2015}, pages = {595{\textendash}602}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Domingues, Alexandre and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez and Sanches, J Miguel} } @article {542, title = {Probabilistic Tissue Characterization for Ultrasound Images}, journal = {Insight Journal}, year = {2015}, abstract = {

This document describes the derivation of the mixture models commonly used in the literature to describe the probabilistic nature of speckle: The Gaussian Mixture Model, the Rayleigh Mixture Model, the Gamma Mixture Model and the Generalized Gamma Mixture Model. New algorithms were implemented using the Insight Toolkit
ITK for tissue characterization by means of a mixture model.


The source code is composed of a set of reusable ITK filters and classes. In addition to an overview of our implementation, we provide the source code, input data, parameters and output data that the authors used for validating the different probabilistic tissue characterization variants described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results.

}, url = {http://www.insight-journal.org/browse/publication/955}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @conference {520, title = {Single Breath Hold Whole Heart Cine MRI With Iterative Groupwise Cardiac Motion Compensation and Sparse Regularization (kt-WiSE)}, booktitle = {Proceedings of the International Society for Magnetic Resonance in Medicine 23}, year = {2015}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Marcos Martin-Fern{\'a}ndez and Claudia Prieto and Carlos Alberola-Lopez} } @article {513, title = {Spatially variant noise estimation in MRI: A homomorphic approach}, journal = {Medical Image Analysis}, volume = {20}, year = {2015}, pages = {184 - 197}, doi = {http://dx.doi.org/10.1016/j.media.2014.11.005}, author = {Santiago Aja-Fern{\'a}ndez and Tomasz Pieciak and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @article {568, title = {Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization}, journal = {PLoS ONE}, volume = {10}, year = {2015}, pages = {e0138910}, doi = {10.1371/journal.pone.0138910}, url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0138910}, author = {Canales-Rodr{\'\i}guez, Erick J. and Daducci, Alessandro and Stamatios N. Sotiropoulos and Caruyer, Emmanuel and Santiago Aja-Fern{\'a}ndez and Radua, Joaquim and Yurramendi Mendizabal, Jes{\'u}s M. and Iturria-Medina, Yasser and Melie-Garc{\'\i}a, Lester and Alem{\'a}n-G{\'o}mez, Yasser and J-P Thiran and Sarr{\'o}, Salvador and Pomarol-Clotet, Edith and Salvador, Raymond} } @conference {656, title = {Tissue and Label Modelling for Segmentation of Scar with Contour Correction in Cardiac DE-CMR Volumes}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2015}, month = {2015}, address = {Madrid, Spain}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez Rodr{\'\i}guez, M Teresa and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Carlos Alberola-Lopez} } @conference {589, title = {Tissue and Label Modelling for Segmentation of Scar with Contour Correction in Cardiac DE-CMR Volumes}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2015}, month = {11/2015}, address = {Madrid, Spain}, abstract = {Most scar segmentation methods for cardiac DE-CMR images are constrained by a previous myocardial segmentation that provides borders for the scar identification. However, the automation of these methods rely on an existing myocardial segmentation from CINE-CMR that is registered to the DE-CMR volume; in this step, however, alignment errors are usually introduced and they carry over to the labeling operation. These errors typically remain unchanged after tissue labeling, so inconsistencies between the two (alignment and labeling) may exist. We explore this issue and present a method that, with the same inputs, identifies the healthy and scarred tissue and selectively corrects the endocardial and epicardial contours depending on the image edges, the estimated probabilistic distributions and the proximity to the aligned myocardial borders. For this, we model the posterior probability of each ROI label with a Bayesian approach that unifies the prior tissue probabilities and the myocardial labels. The maximum a posteriori criterion is used to compute a first DE-CMR label map, which is afterwards refined by a connected component analysis. Preliminary results show better accuracy for the endocardial and epicardial contours, and the segmented scar compares favorably with respect to state of the art methods.}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez Rodr{\'\i}guez, M. T. and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, M. and Carlos Alberola-Lopez} } @article {534, title = {A local fuzzy thresholding methodology for multiregion image segmentation}, journal = {Knowledge-Based Systems}, volume = {83}, year = {2015}, month = {07/2015}, pages = {1-12}, abstract = {

Abstract Thresholding is a direct and simple approach to extract different regions from an image. In its basic formulation, thresholding searches for a global value that maximizes the separation between output classes. The use of a single hard threshold value is precisely the source of important segmentation errors in many scenarios like noisy images or uneven illumination. If no connectivity or closed objects are considered, the method is prone to produce isolated pixels. In this paper a new multiregion thresholding methodology is presented to overcome the common drawbacks of thresholding methods when images are corrupted with artifacts and noise. It is based on relating each pixel in the image to different output centroids via a fuzzy membership function, avoiding any initial hard decision. The starting point of the technique is the definition of the output centroids using a clustering method compatible with most thresholding techniques in the literature. The method makes use of the spatial information through a local aggregation step where the membership degree of each pixel is modified by local information that takes into account the memberships of the surrounding pixels. This makes the method robust to noise and artifacts. The general formulation of the proposed methodology allows the design of spatial aggregations for multiple applications, including the possibility of including heuristic information via a fuzzy inference rule base.

}, issn = {0950-7051}, doi = {http://dx.doi.org/10.1016/j.knosys.2015.02.029}, url = {http://www.sciencedirect.com/science/article/pii/S095070511500129X}, author = {Santiago Aja-Fern{\'a}ndez and Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @proceedings {516, title = {Analysis of coloured noise in received signal strength using the Allan Variance}, volume = {22}, year = {2014}, pages = {994-998}, publisher = {IEEE}, author = {Luo, Chunbo and Pablo Casaseca-de-la-Higuera and McClean, Sally and Parr, Gerard and Grecos, Christos} } @article {martin2014automatic, title = {Automatic detection of wakefulness and rest intervals in actigraphic signals: A data-driven approach}, journal = {Medical engineering \& physics}, volume = {36}, number = {12}, year = {2014}, pages = {1585{\textendash}1592}, publisher = {Elsevier}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Jesus Maria Andres-de-Llano and Jose Ramon Garmendia-Leiza and Susana Alberola-Lopez and Carlos Alberola-Lopez} } @article {curiale2014fully, title = {Fully Automatic Detection of Salient Features in 3-D Transesophageal Images}, journal = {Ultrasound in medicine \& biology}, volume = {40}, year = {2014}, month = {07/2014}, pages = {2868-2884}, publisher = {Elsevier}, chapter = {2868}, author = {Ariel H. Curiale and Haak, Alexander and Gonzalo Vegas-S{\'a}nchez-Ferrero and Ren, Ben and Santiago Aja-Fern{\'a}ndez and Johan G. Bosch} } @inbook {vegas2014gamma, title = {A Gamma Mixture Model for IVUS Imaging}, booktitle = {Multi-Modality Atherosclerosis Imaging and Diagnosis}, year = {2014}, pages = {155{\textendash}171}, publisher = {Springer New York}, organization = {Springer New York}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Marcos Martin-Fernandez and Sanches, J Miguel} } @article {vegas2014gamma, title = {Gamma mixture classifier for plaque detection in intravascular ultrasonic images}, journal = {Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on}, volume = {61}, number = {1}, year = {2014}, pages = {44{\textendash}61}, publisher = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Seabra, Jose and Rodriguez-Leor, Oriol and Serrano-Vida, Angel and Santiago Aja-Fern{\'a}ndez and Palencia, C and Marcos Martin-Fernandez and Sanches, J} } @conference {571, title = {HLS based hardware acceleration on the zynq SoC: A case study for fall detection system}, booktitle = {IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA 2014)}, year = {2014}, address = {Doha, Qatar}, author = {Ait Si Ali, Amine and Siupik, Marek and Amira, Abbes and Bensaali, Faycal and Pablo Casaseca-de-la-Higuera} } @article {476, title = {Localized abnormalities in the cingulum bundle in patients with schizophrenia: A Diffusion Tensor tractography study}, journal = {NeuroImage: Clinical}, volume = {5}, year = {2014}, pages = {93{\textendash}99}, abstract = {

The cingulum bundle (CB) connects gray matter structures of the limbic system and as such has been implicated in the etiology of schizophrenia. There is growing evidence to suggest that the CB is actually comprised of a conglomeration of discrete sub-connections. The present study aimed to use Diffusion Tensor tractography to subdivide the CB into its constituent sub-connections, and to investigate the structural integrity of these sub-connections in patients with schizophrenia and matched healthy controls. Diffusion Tensor Imaging scans were acquired from 24 patients diagnosed with chronic schizophrenia and 26 matched healthy controls. Deterministic tractography was used in conjunction with FreeSurfer-based regions-of-interest to subdivide the CB into 5 sub-connections (I1 to I5). The patients with schizophrenia exhibited subnormal levels of FA in two cingulum sub-connections, specifically the fibers connecting the rostral and caudal anterior cingulate gyrus (I1) and the fibers connecting the isthmus of the cingulate with the parahippocampal cortex (I4). Furthermore, while FA in the I1 sub-connection was correlated with the severity of patients{\textquoteright} positive symptoms (specifically hallucinations and delusions), FA in the I4 sub-connection was correlated with the severity of patients{\textquoteright} negative symptoms (specifically affective flattening and anhedonia/asociality). These results support the notion that the CB is a conglomeration of structurally interconnected yet functionally distinct sub-connections, of which only a subset are abnormal in patients with schizophrenia. Furthermore, while acknowledging the fact that the present study only investigated the CB, these results suggest that the positive and negative symptoms of schizophrenia may have distinct neurobiological underpinnings.

}, author = {Whitford, Thomas J and Lee, Sun Woo and Oh, Jungsu S and Rodrigo de Luis-Garc{\'\i}a and Savadjiev, Peter and Alvarado, Jorge L and Carl-Fredik Westin and Niznikiewicz, Margaret and Nestor, Paul G and McCarley, Robert W} } @conference {426, title = {MOWHARP: Multi-Oriented Windowed HARP Reconstruction for Robust Strain Imaging}, booktitle = {Proceedings of the International Society for Magnetic Resonance in Medicine 22}, year = {2014}, author = {Lucilio Cordero-Grande and J Royuela-del-Val and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {445, title = {Multi-stencil streamline fast marching: a general 3D framework to determine myocardial thickness and transmurality in late enhancement images}, journal = {Medical Imaging, IEEE Transactions on}, volume = {33}, year = {2014}, pages = {23{\textendash}37}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and A. Revilla-Orodea and Perez, M. T. and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {aja2014noise, title = {Noise estimation in parallel MRI: GRAPPA and SENSE}, journal = {Magnetic resonance imaging}, volume = {32}, number = {3}, year = {2014}, pages = {281{\textendash}290}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega} } @article {canales2014spherical, title = {Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and total variation spatial regularization}, journal = {arXiv preprint arXiv:1410.6353}, year = {2014}, author = {Canales-Rodr{\'\i}guez, Erick J and Daducci, Alessandro and Stamatios N. Sotiropoulos and Caruyer, Emmanuel and Santiago Aja-Fern{\'a}ndez and Radua, Joaquim and Mendizabal, Yosu Yurramendi and Iturria-Medina, Yasser and Melie-Garc{\'\i}a, Lester and Alem{\'a}n-G{\'o}mez, Yasser} } @article {aja2014statistical, title = {Statistical Noise Analysis in SENSE Parallel MRI}, journal = {arXiv preprint arXiv:1402.4067}, year = {2014}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega} } @book {676, title = {Sunflowers: growth and development, environmental influences and pests/diseases.}, year = {2014}, pages = {323}, publisher = {Nova Science Publishers}, organization = {Nova Science Publishers}, address = {New York}, abstract = {

We are all well aware that the importance of the sunflower (Helianthus Annus) as a crop has increased significantly in recent years, not only in the food industry but also as a natural energy resource in oil production. I am, thus, very pleased to be able to present this comprehensive monograph on a wide range of important issues regarding sunflowers, with an emphasis on environmental influences, pests and diseases in order to maximise production whilst minimising costs.

Contributors where selected based on their proven experience in the field of sunflowers. Contributors submitted an extended abstract that was assessed for relevance. They were then invited to contribute draft chapters. Each chapter underwent a stringent and thorough peer review process by other experts in the field, with final approval by the editor who, thus, was able to balance the topics from all contributors.

The book contains important original results. Each chapter deals with a different topic, and draws, where appropriate, from studies and results previously published by the authors. Authors were encouraged to complement their writing with original and high quality graphs, charts, tables, figures, pictures and photographs.

It{\textquoteright}s my honour and pleasure to acknowledge the rigorous work carried out by all authors in this book, and at the same time I am very grateful to them for trusting me in leading this project in the role of the editor of their work. My thanks also go to the anonymous reviewers who contributed their time so generously to this book, and without whom it would not exist.

I am also very grateful to Nova Science Pubs. for inviting me to lead this book, and thank them for the help and coverage provided during the whole time that this project lasted.

I really do hope that you find this book of interest and wish you enjoy its reading as much as I have done through the whole editing process and as much I am sure all authors have done while writing it.

}, keywords = {Leaf classification, Sunflower, desease, environmental, pest}, isbn = {978-1-63117.348-6}, doi = {https://www.scopus.com/record/display.uri?eid=2-s2.0-84948981604\&origin=resultslist\&sort=plf-f\&src=s\&sid=6fdffa7042d279955cdde5960c4dc452\&sot=autdocs\&sdt=autdocs\&sl=17\&s=AU-ID\%287103041133\%29\&relpos=4\&citeCnt=0\&searchTerm=}, url = {https://www.amazon.com/Sunflowers-Development-Environmental-Influences-Botanical/dp/1631173472}, author = {J I Arribas} } @article {de2014white, title = {White matter abnormalities in chronic migraine patients are located in anterior corpus callosum: study using a new automatic tractography selection method}, journal = {EUROPEAN JOURNAL OF NEUROLOGY}, volume = {21}, year = {2014}, pages = {51{\textendash}51}, publisher = {WILEY-BLACKWELL 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, author = {De la Cruz, C and {\'A}ngel L. Guerrero and Penas, ML and Daniel Argibay-Qui{\~n}ones and Jose M Sierra and Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a} } @conference {570, title = {An efficient user-customisable multiresolution classifier fall detection and diagnostic system}, booktitle = {26th IEEE International Conference on Microelectronics (ICM 2014)}, year = {2014}, address = {Doha, Qatar}, author = {Gibson, Ryan M and Amira, Abbes and Pablo Casaseca-de-la-Higuera and Ramzan, Naeem and Pervez, Zeeshan} } @conference {447, title = {A stochastic modelling framework for the reconstruction of cardiovascular signals}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE}, volume = {36}, year = {2014}, pages = {676-679}, publisher = {IEEE}, organization = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Amira, Abbes and Luo, Chunbo and Grecos, Christos and Carlos Alberola-Lopez} } @article {ruiz2013advanced, title = {Advanced signal processing methods for biomedical imaging}, journal = {International journal of biomedical imaging}, volume = {2013}, year = {2013}, publisher = {Hindawi Publishing Corporation}, author = {Juan Ruiz-Alzola and Carlos Alberola-Lopez and Carl-Fredik Westin} } @conference {vegas2013anisotropic, title = {Anisotropic diffusion filtering for correlated multiple-coil MRI}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE}, year = {2013}, pages = {2956{\textendash}2959}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Gabriel Ramos-Llorden and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @conference {gonzalez2013applying, title = {Applying a parametric approach for the task of nonstationary noise removal with missing information}, booktitle = {Computational Cybernetics (ICCC), 2013 IEEE 9th International Conference on}, year = {2013}, pages = {23{\textendash}28}, publisher = {IEEE}, organization = {IEEE}, author = {Luis Gonz{\'a}lez-Jaime and Nachtegeal, Mike and Kerre, Etienne and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @conference {444, title = {Assessment of the fibrotic myocardial tissue mechanics by image processing}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and T. Sevilla-Ruiz and Revilla, Ana and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {de2013atlas, title = {Atlas-based segmentation of white matter structures from DTI using tensor invariants and orientation}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE}, year = {2013}, pages = {503{\textendash}506}, publisher = {IEEE}, organization = {IEEE}, author = {Rodrigo de Luis-Garc{\'\i}a and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {443, title = {Classification of delayed enhancement scar islands by means of their local subendocardial transmurality}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and T. Sevilla-Ruiz and P{\'e}rez, Teresa and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {436, title = {Comparativa entre distribuciones alpha-estables para modelar tasas de transferencia obtenidas a partir de registros de SNMP y NetFlow}, booktitle = {Jornadas de Ingenier{\'\i}a Telem{\'a}tica (JITEL)}, year = {2013}, publisher = {Asociaci{\'o}n de Telem{\'a}tica (ATEL)}, organization = {Asociaci{\'o}n de Telem{\'a}tica (ATEL)}, address = {Granada, Spain}, author = {Stoppa, Matteo and L{\'o}pez-de-Vergara-M{\'e}ndez, Jorge E. and Federico Simmross-Wattenberg and Garc{\'\i}a-Dorado, Jos{\'e} Luis} } @proceedings {martin2014ecg, title = {ECG Signal Reconstruction Based on Stochastic Joint-Modeling of the ECG and the PPG Signals}, year = {2013}, pages = {989{\textendash}992}, publisher = {Springer International Publishing}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {aja2013effective, title = {Effective noise estimation and filtering from correlated multiple-coil MR data}, journal = {Magnetic resonance imaging}, volume = {31}, number = {2}, year = {2013}, pages = {272{\textendash}285}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and V{\'e}ronique Brion and Antonio Trist{\'a}n-Vega} } @proceedings {ramos2014fast, title = {Fast Anisotropic Speckle Filter for Ultrasound Medical Images}, year = {2013}, pages = {253{\textendash}256}, publisher = {Springer International Publishing}, author = {Gabriel Ramos-Llorden and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {de2013geometrical, title = {Geometrical constraints for robust tractography selection}, journal = {NeuroImage}, volume = {81}, year = {2013}, pages = {26{\textendash}48}, publisher = {Academic Press}, author = {Rodrigo de Luis-Garc{\'\i}a and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {cordero2013groupwise, title = {Groupwise elastic registration by a new sparsity-promoting metric: application to the alignment of cardiac magnetic resonance perfusion images}, journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on}, volume = {35}, number = {11}, year = {2013}, pages = {2638{\textendash}2650}, publisher = {IEEE}, author = {Lucilio Cordero-Grande and S. Merino-Caviedes and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @inbook {garcia2013homeomorphic, title = {Homeomorphic Geometrical Transform for Collision Response in Surgical Simulation}, booktitle = {Pattern Recognition and Image Analysis}, year = {2013}, pages = {433{\textendash}440}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Ver{\'o}nica Garc{\'\i}a-P{\'e}rez and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {garmendia2013influence, title = {Influence of institutionalization on the sleep pattern in elderly population}, journal = {Sleep Medicine}, volume = {14}, year = {2013}, pages = {e181{\textendash}e182}, publisher = {Elsevier}, author = {Jose Ramon Garmendia-Leiza and Aguilar Garcia, M and Jes{\'u}s Mar{\'\i}a And De Llano and Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @conference {cordero2013integration, title = {Integration of biomechanical properties in a Markov random field: Application to myocardial motion estimation in cardiomyopathy patients}, booktitle = {Quantitative Medical Imaging}, year = {2013}, pages = {QW2G{\textendash}1}, publisher = {Optical Society of America}, organization = {Optical Society of America}, author = {Lucilio Cordero-Grande and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {tristan2013merging, title = {Merging squared-magnitude approaches to DWI denoising: An adaptive Wiener filter tuned to the anatomical contents of the image}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE}, year = {2013}, pages = {507{\textendash}510}, publisher = {IEEE}, organization = {IEEE}, author = {Antonio Trist{\'a}n-Vega and V{\'e}ronique Brion and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {brion2013noise, title = {Noise correction for HARDI and HYDI data obtained with multi-channel coils and Sum of Squares reconstruction: An anisotropic extension of the LMMSE}, journal = {Magnetic resonance imaging}, volume = {31}, number = {8}, year = {2013}, pages = {1360{\textendash}1371}, publisher = {Elsevier}, author = {V{\'e}ronique Brion and Poupon, Cyril and Riff, Olivier and Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Mangin, Jean-Fran{\c c}ois and Le Bihan, Denis and Poupon, Fabrice} } @conference {aja2013noise, title = {Noise estimation in magnetic resonance SENSE reconstructed data}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE}, year = {2013}, pages = {1104{\textendash}1107}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega} } @inbook {gonzalez2013parametric, title = {Parametric Image Restoration Using Consensus: An Application to Nonstationary Noise Filtering}, booktitle = {Pattern Recognition and Image Analysis}, year = {2013}, pages = {358{\textendash}365}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Luis Gonz{\'a}lez-Jaime and Nachtegeal, Mike and Kerre, Etienne and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @conference {446, title = {Probabilistic modeling of the oxygen saturation pattern for the detection of anomalies during clinical interventions}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @conference {aja2013quantitative, title = {Quantitative Diffusion MRI in the Presence of Noise: Effects of Filtering and Fitting Technique}, booktitle = {Quantitative Medical Imaging}, year = {2013}, pages = {QTu2G{\textendash}2}, publisher = {Optical Society of America}, organization = {Optical Society of America}, author = {Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez and Hernando, Diego} } @conference {aja2013robust, title = {Robust estimation of MRI myocardial perfusion parameters}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE}, year = {2013}, pages = {4382{\textendash}4385}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @inbook {curiale2013speckle, title = {Speckle tracking in interpolated echocardiography to estimate heart motion}, booktitle = {Functional Imaging and Modeling of the Heart}, year = {2013}, pages = {325{\textendash}333}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {martin2013stochastic, title = {Stochastic Modeling of the PPG Signal: A Synthesis-by-Analysis Approach With Applications}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {60}, number = {9}, year = {2013}, pages = {2432{\textendash}2441}, publisher = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {curiale2013strain, title = {Strain rate tensor estimation from echocardiography for quantitative assessment of functional mitral regurgitation}, booktitle = {Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on}, year = {2013}, pages = {788{\textendash}791}, publisher = {IEEE}, organization = {IEEE}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Teresa P{\'e}rez-Sanz and Santiago Aja-Fern{\'a}ndez} } @article {martin2013utility, title = {Utility of the statistical and nonlinear analysis for the actigraphic sleep pattern characterization}, journal = {Sleep Medicine}, volume = {14}, year = {2013}, pages = {e181}, publisher = {Elsevier}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez and Jose Ramon Garmendia-Leiza and Jes{\'u}s Mar{\'\i}a And De Llano and Susana Alberola Lopez} } @article {cordero2013magnetic, title = {A magnetic resonance software simulator for the evaluation of myocardial deformation estimation}, journal = {Medical engineering \& physics}, volume = {35}, number = {9}, year = {2013}, pages = {1331{\textendash}1340}, publisher = {Elsevier}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {cordero20123d, title = {3D fusion of cine and late-enhanced cardiac magnetic resonance images}, booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on}, year = {2012}, pages = {286{\textendash}289}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and S. Merino-Caviedes and Alba, X{\`e}nia and Figueras i Ventura, RM and Frangi, Alejandro F and Carlos Alberola-Lopez} } @conference {vegas2012anisotropic, title = {Anisotropic LMMSE denoising of MRI based on statistical tissue models}, booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on}, year = {2012}, pages = {1519{\textendash}1522}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Cesar Palencia and Deriche, Rachid} } @conference {casaseca2012automatic, title = {Automatic diagnosis of ADHD based on multichannel nonlinear analysis of actimetry registries}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE}, year = {2012}, pages = {4204{\textendash}4207}, publisher = {IEEE}, organization = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Diego Mart{\'\i}n-Mart{\'\i}nez and Susana Alberola-Lopez and Jesus Maria Andres-de-Llano and L{\'o}pez-Villalobos, Jos{\'e} Antonio and JR Garmendia-Leiza and Carlos Alberola-Lopez} } @conference {435, title = {Caracterizaci{\'o}n de speckle con modelos de cola pesada}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2012}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, organization = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {San Sebasti{\'a}n, Espa{\~n}a}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Palencia-de-Lara, C{\'e}sar and Carlos Alberola-Lopez} } @conference {martin2012cardiovascular, title = {Cardiovascular signal reconstruction based on shape modelling and non-stationary temporal modelling}, booktitle = {Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European}, year = {2012}, pages = {1826{\textendash}1830}, publisher = {IEEE}, organization = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {tristan2012deblurring, title = {Deblurring of probabilistic ODFs in quantitative diffusion MRI}, booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on}, year = {2012}, pages = {932{\textendash}935}, publisher = {IEEE}, organization = {IEEE}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin} } @conference {462, title = {Detecci{\'o}n autom{\'a}tica del ventr{{\'\i}culo derecho en im{\'a}genes de resonancia magn{\'e}tica cardiaca 3D}, booktitle = {CASEIB2012, San Sebasti{\'a}n, Espana}, year = {2012}, author = {D{\'\i}az-Rodr{\'\i}guez, JM and Lucilio Cordero-Grande and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {434, title = {Dise{\~n}o e implementaci{\'o}n de plugins en el entorno GIMIAS para procesado y visualizaci{\'o}n de se{\~n}ales electrofisiol{\'o}gicas asociadas a problemas cardiovasculares}, booktitle = {Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2012}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, organization = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {San Sebasti{\'a}n, Espa{\~n}a}, author = {Mart{\'\i}n-Hern{\'a}ndez, Noelia and J Royuela-del-Val and Ver{\'o}nica Garc{\'\i}a-P{\'e}rez and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {tristan2012efficient, title = {Efficient and robust nonlocal means denoising of MR data based on salient features matching}, journal = {Computer methods and programs in biomedicine}, volume = {105}, number = {2}, year = {2012}, pages = {131{\textendash}144}, publisher = {Elsevier}, author = {Antonio Trist{\'a}n-Vega and Ver{\'o}nica Garc{\'\i}a-P{\'e}rez and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin} } @article {vegas2012generalized, title = {A Generalized Gamma Mixture Model for Ultrasonic Tissue Characterization}, journal = {Computational and mathematical methods in medicine}, volume = {2012}, year = {2012}, publisher = {Hindawi Publishing Corporation}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez and Cesar Palencia and Marcos Martin-Fernandez} } @article {aja2012influence, title = {Influence of noise correlation in multiple-coil statistical models with sum of squares reconstruction}, journal = {Magnetic Resonance in Medicine}, volume = {67}, number = {2}, year = {2012}, pages = {580{\textendash}585}, publisher = {Wiley Subscription Services, Inc., A Wiley Company}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega} } @article {tristan2012least, title = {Least squares for diffusion tensor estimation revisited: Propagation of uncertainty with Rician and non-Rician signals}, journal = {NeuroImage}, volume = {59}, number = {4}, year = {2012}, pages = {4032{\textendash}4043}, publisher = {Academic Press}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin} } @conference {aja2012mri, title = {A MRI phantom for cardiac perfusion simulation}, booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on}, year = {2012}, pages = {638{\textendash}641}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Lucilio Cordero-Grande and Carlos Alberola-Lopez} } @article {cordero2012markov, title = {A Markov random field approach for topology-preserving registration: Application to object-based tomographic image interpolation}, journal = {Image Processing, IEEE Transactions on}, volume = {21}, number = {4}, year = {2012}, pages = {2047{\textendash}2061}, publisher = {IEEE}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @proceedings {580, title = {M{\'e}todos de an{\'a}lisis autom{\'a}tico de la actividad diaria del ni{\~n}o con TDAH. Mesa Redonda. Ponencia Invitada}, volume = {61}, year = {2012}, pages = {43-49}, address = {Granada, Spain}, author = {Pablo Casaseca-de-la-Higuera and Diego Mart{\'\i}n-Mart{\'\i}nez and Susana Alberola-Lopez and Jesus Maria Andres-de-Llano and L{\'o}pez-Villalobos, Jos{\'e} Antonio and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @article {martin2012nonlinear, title = {Nonlinear analysis of actigraphic signals for the assessment of the attention-deficit/hyperactivity disorder (ADHD)}, journal = {Medical engineering \& physics}, volume = {34}, number = {9}, year = {2012}, pages = {1317{\textendash}1329}, publisher = {Elsevier}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Susana Alberola-Lopez and Jesus Maria Andres-de-Llano and L{\'o}pez-Villalobos, JA and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @article {casaseca2012optimal, title = {Optimal real-time estimation in diffusion tensor imaging}, journal = {Magnetic resonance imaging}, volume = {30}, number = {4}, year = {2012}, pages = {506{\textendash}517}, publisher = {Elsevier}, author = {Pablo Casaseca-de-la-Higuera and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Carl-Fredik Westin and Raul San Jose-Estepar} } @inbook {cardenes2012quantitative, title = {Quantitative Analysis of Pyramidal Tracts in Brain Tumor Patients Using Diffusion Tensor Imaging}, booktitle = {Tumors of the Central Nervous System, Volume 4}, year = {2012}, pages = {143{\textendash}152}, publisher = {Springer Netherlands}, organization = {Springer Netherlands}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Sarabia-Herrero, Rosario and Daniel Argibay-Qui{\~n}ones and Marcos Martin-Fernandez} } @proceedings {579, title = {Reconstrucci{\'o}n de la Se{\~n}al Respiratoria basada en Modelo Conjunto con la Se{\~n}al de Per{\'\i}odo Card{\'\i}aco}, year = {2012}, address = {San Sebasti{\'a}n, Spain}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {575, title = {Relation between Myocardial Infarction and Cyrcadian Rhythm in Patients Attended in a Prehospital Emergency Service}, journal = {Medicina Cl{\'\i}nica}, volume = {139}, year = {2012}, pages = {515-521}, chapter = {551}, author = {Barneto-Valero, Mar{\'\i}a Cristina and Jose Ramon Garmendia-Leiza and Julio Ardura-Fernández and Pablo Casaseca-de-la-Higuera and Jesus Maria Andres-de-Llano and Corral-Torres, Ervigio} } @proceedings {581, title = {TDAH en atenci{\'o}n primaria: Registro de la Actividad mediante actimetr{\'\i}a ambulatoria. Mesa Redonda. Ponencia Invitada}, volume = {61}, year = {2012}, pages = {34-39}, address = {Granada, Spain}, author = {Susana Alberola-Lopez and Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Irene Casares-Alonso and Isabel P{\'e}rez-Garc{\'\i}a and Alfredo Cano-Garcinu{\~n}o and L{\'o}pez-Villalobos, Jos{\'e} Antonio and Ruiz, F.C. and Jesus Maria Andres-de-Llano and Carlos Alberola-Lopez and Julio Ardura-Fernández} } @inbook {432, title = {Ubiquitous tele-monitoring kit (UTK): measuring physiological signals anywhere at anytime}, booktitle = {Ambient Assisted Living and Home Care}, year = {2012}, pages = {183{\textendash}191}, publisher = {Springer}, organization = {Springer}, author = {Marcos-Lagunar, Carlos and Cavero-Barca, Carlos and Quintero-Padr{\'o}n, Ana Mar{\'\i}a and Planes, Xavier and Federico Simmross-Wattenberg and Carlos Alberola-Lopez and Marcos Martin-Fernandez and Mart{\'\i}n-Hern{\'a}ndez, Noelia and Calder{\'o}n-Oliveras, Enric and Corral-Herranz, Javier and Gonz{\'a}lez-Mart{\'\i}nez, A. and Huguet, Jordi and Aguilar, Rosal{\'\i}a} } @proceedings {582, title = {Validez de los criterios DSM-IV en el diagnostico del TDAH. Nuevas perspectivas de investigaci{\'o}n. Mesa Redonda. Ponencia Invitada}, volume = {61}, year = {2012}, pages = {39-43}, address = {Granada, Spain}, author = {L{\'o}pez-Villalobos, Jos{\'e} Antonio and Jesus Maria Andres-de-Llano and Susana Alberola-Lopez and Pablo Casaseca-de-la-Higuera and Diego Mart{\'\i}n-Mart{\'\i}nez and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @inbook {de2012choice, title = {On the choice of a tensor distance for DTI white matter segmentation}, booktitle = {New Developments in the Visualization and Processing of Tensor Fields}, year = {2012}, pages = {283{\textendash}306}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez and Carl-Fredik Westin} } @article {vegas2012direct, title = {A direct calculation of moments of the sample variance}, journal = {Mathematics and Computers in Simulation}, volume = {82}, number = {5}, year = {2012}, pages = {790{\textendash}804}, publisher = {North-Holland}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Palencia, C{\'e}sar} } @proceedings {586, title = {Algoritmo de Compresi{\'o}n de Se{\~n}ales de ECG basado en un Modelo de S{\'\i}ntesis. An{\'a}lisis Comparativo}, volume = {29}, year = {2011}, pages = {733-736}, address = {C{\'a}ceres, Spain}, author = {V{\'\i}ctor Mart{\'\i}nez-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {193, title = {Anomaly detection in network traffic based on statistical inference and alpha-stable modeling}, journal = {Dependable and Secure Computing, IEEE Transactions on}, volume = {8}, year = {2011}, pages = {494{\textendash}509}, author = {Federico Simmross-Wattenberg and Juan Ignacio Asensio-P{\'e}rez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Yannis A Dimitriadis and Carlos Alberola-Lopez} } @proceedings {576, title = {Automatic diagnosis of ADHD based on nonlinear analysis of actimetry registries}, volume = {32}, year = {2011}, pages = {685-688}, address = {Prague, Czech Rep.}, keywords = {ADHD, ADHD automatic diagnosis, Activity/Rest Detection, Attention-Deficit Hyperactivity Disorder, Automatic Diagnosis System, Central Tendency Measure, Feature extraction, Histograms, Indexes, Noise, Pediatrics, Regularity Assessment, Sleep, USA Councils, Wrist, actimetry registries, adolescence, automatic activity/rest detection filter, biomedical measurement, childhood, feature extraction module, medical disorders, medical signal processing, mental health problem, neurophysiology, nonlinear analysis, nonlinear regularity quantification, paediatrics, pathology, signal processing methods}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Susana Alberola-Lopez and L{\'o}pez-Villalobos, J.A. and Ruiz, F.C. and Jesus Maria Andres-de-Llano and Jose Ramon Garmendia-Leiza and Julio Ardura-Fernández} } @article {garmendia2011beta, title = {Beta blocker therapy modifies circadian rhythm acute myocardial infarction}, journal = {International journal of cardiology}, volume = {147}, number = {2}, year = {2011}, pages = {316{\textendash}317}, publisher = {Elsevier}, author = {Jose Ramon Garmendia-Leiza and Jesus Maria Andres-de-Llano and Julio Ardura-Fernández and Juan Bautista Lopez-Messa and Carlos Alberola-Lopez and Pablo Casaseca-de-la-Higuera} } @article {Trist{\'a}nVega2011586, title = {Comments on: A locally constrained radial basis function for registration and warping of images}, journal = {Pattern Recognition Letters}, volume = {32}, number = {4}, year = {2011}, pages = {586 - 589}, keywords = {Interpolation kernels}, issn = {0167-8655}, doi = {http://dx.doi.org/10.1016/j.patrec.2010.11.012}, url = {http://www.sciencedirect.com/science/article/pii/S0167865510003788}, author = {Antonio Trist{\'a}n-Vega and Ver{\'o}nica Garc{\'\i}a-P{\'e}rez} } @conference {405, title = {Cuantificaci{\'o}n de la insuficiencia mitral funcional mediante el esfuerzo y la velocidad del miocardio}, booktitle = {XXIX Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2011}, address = {Centro de Cirug{\'\i}a de M{\'\i}nima Invasi{\'o}n Jes{\'u}s Us{\'o}n}, author = {Ariel H. Curiale and S{\'a}nchez-Ferrero, G Vegas and Teresa P{\'e}rez-Sanz and Santiago Aja-Fern{\'a}ndez} } @conference {arenillas2011diffusion, title = {Diffusion Tensor Imaging (DTI) Monitoring Of Motor Function Recovery After Middle Cerebral Artery Infarction: Searching For A DTI-Marker Of Neurorepair}, booktitle = {STROKE}, volume = {42}, number = {3}, year = {2011}, pages = {E119{\textendash}E119}, publisher = {LIPPINCOTT WILLIAMS \& WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}, organization = {LIPPINCOTT WILLIAMS \& WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}, author = {Juan F Arenillas and Daniel Argibay-Qui{\~n}ones and Garcia-Bermejo, Pablo and Calleja, Ana I and Diego Mart{\'\i}n-Mart{\'\i}nez and Jose M Sierra and Juan Jos{\'e} Fuertes-Alija and Marcos Martin-Fernandez} } @article {408, title = {Evaluation of the use of low-cost GPS receivers in the autonomous guidance of agricultural tractors}, journal = {Spanish Journal of Agricultural Research}, volume = {9}, year = {2011}, pages = {377-388}, abstract = {

This paper evaluates the use of low-cost global positioning system (GPS) receivers in the autonomous guidance of agricultural tractors. An autonomous guidance system was installed in a 6400 John Deere agricultural tractor. A lowcost GPS receiver was used as positioning sensor. Three different control laws were implemented in order to evaluate the autonomous guidance of the tractor with the low-cost receiver. The guidance was experimentally tested with the tracking of straight trajectories and with the step response. The total guidance error was obtained from the receiver accuracy and from the guidance error. For the evaluation of the receiver{\textquoteright}s accuracy, positioning data from several lowcost receivers were recorded and analyzed. For the evaluation of the guidance error, tests were performed with each control law at three different speeds. The conclusions obtained were that relative accuracy of low-cost receivers decreases with the time; that for an interval lower than 15 min, the error usually remains below 1 m; that all the control laws have a similar behavior and it is conditioned by the control law adjustment; that automatic guidance with lowcost receivers is possible with speeds that went up to 9 km h -1; and finally, that the total error in the guidance is mainly determined by the receiver{\textquoteright}s accuracy.

}, issn = {1695971X}, doi = {https://doi.org/10.5424/sjar/20110902-088-10}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79959669468\&partnerID=40\&md5=774d42717ec127c9a6c5e25864da9722}, author = {Sergio Alonso-Garcia and Jaime Gomez-Gil and J I Arribas} } @article {de2011gaussian, title = {Gaussian mixtures on tensor fields for segmentation: Applications to medical imaging}, journal = {Computerized Medical Imaging and Graphics}, volume = {35}, number = {1}, year = {2011}, pages = {16{\textendash}30}, publisher = {Elsevier}, author = {Rodrigo de Luis-Garc{\'\i}a and Carl-Fredik Westin and Carlos Alberola-Lopez} } @proceedings {cordero2011groupwise, title = {Groupwise myocardial alignment in magnetic resonance perfusion sequences}, year = {2011}, pages = {437{\textendash}440}, author = {Lucilio Cordero-Grande and S. Merino-Caviedes and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {cordero2011improving, title = {Improving Harmonic Phase Imaging by the Windowed Fourier Transform}, booktitle = {Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on}, year = {2011}, pages = {520{\textendash}523}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @conference {585, title = {Intra Heartbeat Variability as a Tool for Cardiovascular Diagnosis and Monitoring}, booktitle = {XXIX Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, volume = {29}, year = {2011}, pages = {343-346}, address = {C{\'a}ceres, Spain}, author = {Daniel Ruiz-Aguado and Marcos Martin-Fern{\'a}ndez and J Royuela-del-Val and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @article {424, title = {Leaf classification in sunflower crops by computer vision and neural networks}, journal = {Computers and Electronics in Agriculture}, volume = {78}, year = {2011}, pages = {9-18}, abstract = {

In this article, we present an automatic leaves image classification system for sunflower crops using neural networks, which could be used in selective herbicide applications. The system is comprised of four main stages. First, a segmentation based on rgb color space is performed. Second, many different features are detected and then extracted from the segmented image. Third, the most discriminable set of features are selected. Finally, the Generalized Softmax Perceptron (GSP) neural network architecture is used in conjunction with the recently proposed Posterior Probability Model Selection (PPMS) algorithm for complexity selection in order to select the leaves in an image and then classify them either as sunflower or non-sunflower. The experimental results show that the proposed system achieves a high level of accuracy with only five selected discriminative features obtaining an average Correct Classification Rate of 85\% and an area under the receiver operation curve over 90\%, for the test set. {\^A}{\textcopyright} 2011 Elsevier B.V.

}, keywords = {Classification rates, Computer vision, Crops, Discriminative features, Generalized softmax perceptron, Helianthus, Herbicide application, Herbicides, Image classification, Image classification systems, Leaf classification, Learning machines, Model selection, Network architecture, Neural networks, Posterior probability, RGB color space, Segmented images, Sunflower, Test sets, accuracy assessment, agricultural technology, algorithm, artificial neural network, automation, dicotyledon, experimental study, herbicide, segmentation}, issn = {01681699}, doi = {10.1016/j.compag.2011.05.007}, url = {https://www.sciencedirect.com/science/article/pii/S0168169911001220}, author = {J I Arribas and G V Sanchez-Ferrero and G Ruiz-Ruiz and Jaime Gomez-Gil} } @proceedings {584, title = {Modelado Estad{\'\i}stico de Se{\~n}ales Fotopletismogr{\'a}ficas para la Construcci{\'o}n de Atlas Poblacionales Orientados a la Evaluaci{\'o}n y Seguimiento del Remodelado Cardiovascular}, volume = {29}, year = {2011}, pages = {607-610}, address = {C{\'a}ceres, Spain}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n Fern{\'a}ndez, Marcos and Carlos Alberola-Lopez} } @conference {aja2011noise, title = {Noise estimation in MR GRAPPA reconstructed data}, booktitle = {Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on}, year = {2011}, pages = {1815{\textendash}1818}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega} } @inbook {brion2011parallel, title = {Parallel MRI noise correction: an extension of the LMMSE to non central $\chi$ distributions}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2011}, year = {2011}, pages = {226{\textendash}233}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {V{\'e}ronique Brion and Poupon, Cyril and Riff, Olivier and Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Mangin, Jean-Fran{\c c}ois and Le Bihan, Denis and Poupon, Fabrice} } @conference {vegas2011realistic, title = {Realistic log-compressed law for ultrasound image recovery}, booktitle = {Image Processing (ICIP), 2011 18th IEEE International Conference on}, year = {2011}, pages = {2029{\textendash}2032}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Lucilio Cordero-Grande and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Cesar Palencia} } @proceedings {barrio2011saturn2, title = {SATURN2: An Improved Software Tool for Neuroimaging Analysis}, year = {2011}, author = {Gonzalo Barrio-Arranz and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Marcos Martin-Fernandez} } @article {aja2011statistical, title = {Statistical noise analysis in GRAPPA using a parametrized noncentral Chi approximation model}, journal = {Magnetic resonance in medicine}, volume = {65}, number = {4}, year = {2011}, pages = {1195{\textendash}1206}, publisher = {Wiley Subscription Services, Inc., A Wiley Company}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and W Scott Hoge} } @inbook {cordero2011topology, title = {Topology-preserving registration: a solution via graph cuts}, booktitle = {Combinatorial Image Analysis}, year = {2011}, pages = {420{\textendash}431}, publisher = {Springer}, organization = {Springer}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @proceedings {merino2011transmurality, title = {Transmurality Maps in Late Enhancement Cardiac Magnetic Resonance Imaging by a New Radial Fast Marching Method}, year = {2011}, pages = {211{\textendash}214}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez, M Teresa and Marcos Martin-Fernandez} } @article {cordero2011unsupervised, title = {Unsupervised 4D myocardium segmentation with a Markov Random Field based deformable model}, journal = {Medical image analysis}, volume = {15}, number = {3}, year = {2011}, pages = {283{\textendash}301}, publisher = {Elsevier}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Alberto San-Rom{\'a}n-Calvar, J and A. Revilla-Orodea and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {aja2010background, title = {About the background distribution in MR data: a local variance study}, journal = {Magnetic resonance imaging}, volume = {28}, number = {5}, year = {2010}, pages = {739{\textendash}752}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega} } @article {cardenes2010analysis, title = {Analysis of the pyramidal tract in tumor patients using diffusion tensor imaging}, journal = {NeuroImage}, volume = {50}, number = {1}, year = {2010}, pages = {27{\textendash}39}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Sarabia-Herrero, Rosario and Rodr{\'\i}guez-Velasco, Margarita and Juan Jos{\'e} Fuertes-Alija and Marcos Martin-Fernandez} } @article {423, title = {Automatic bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from fMRI data}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {57}, year = {2010}, pages = {2850-2860}, abstract = {

We present a method for supervised, automatic, and reliable classification of healthy controls, patients with bipolar disorder, and patients with schizophrenia using brain imaging data. The method uses four supervised classification learning machines trained with a stochastic gradient learning rule based on the minimization of KullbackLeibler divergence and an optimal model complexity search through posterior probability estimation. Prior to classification, given the high dimensionality of functional MRI (fMRI) data, a dimension reduction stage comprising two steps is performed: first, a one-sample univariate t-test mean-difference Tscore approach is used to reduce the number of significant discriminative functional activated voxels, and then singular value decomposition is performed to further reduce the dimension of the input patterns to a number comparable to the limited number of subjects available for each of the three classes. Experimental results using functional brain imaging (fMRI) data include receiver operation characteristic curves for the three-way classifier with area under curve values around 0.82, 0.89, and 0.90 for healthy control versus nonhealthy, bipolar disorder versus nonbipolar, and schizophrenia patients versus nonschizophrenia binary problems, respectively. The average three-way correct classification rate (CCR) is in the range of 70\%-72\%, for the test set, remaining close to the estimated Bayesian optimal CCR theoretical upper bound of about 80\%, estimated from the one nearest-neighbor classifier over the same data. {\^A}{\textcopyright} 2010 IEEE.

}, keywords = {Algorithms, Artificial Intelligence, Bayes Theorem, Bayesian learning, Bayesian networks, Biological, Brain, Case-Control Studies, Classifiers, Computer-Assisted, Diseases, Functional MRI (fMRI), Humans, Learning machines, Learning systems, Magnetic Resonance Imaging, Models, Operation characteristic, Optimization, ROC Curve, Reproducibility of Results, Signal Processing, Singular value decomposition, Statistical tests, Stochastic models, Student t test, area under the curve, article, bipolar disorder, classification, controlled study, functional magnetic resonance imaging, human, machine learning, major clinical study, neuroimaging, patient coding, receiver operating characteristic, reliability, schizophrenia}, issn = {00189294}, doi = {10.1109/TBME.2010.2080679}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-78649311169\&partnerID=40\&md5=d3b90f1a3ee4ef209d131ef986e142db}, author = {J I Arribas and V D Calhoun and T Adali} } @proceedings {515, title = {Characterization of activity epochs in actimetric registries for infantile colic diagnosis: Identification and feature extraction based on wavelets and symbolic dynamics}, volume = {32}, year = {2010}, pages = {2383-2386}, publisher = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Gonzalo Vegas-S{\'a}nchez-Ferrero and Lucilio Cordero-Grande and Jesus Maria Andres-de-Llano and Jose Ramon Garmendia-Leiza and Julio Ardura-Fernández} } @conference {aja2010dwi, title = {DWI acquisition schemes and diffusion tensor estimation: a simulation-based study}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE}, year = {2010}, pages = {3317{\textendash}3320}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Pablo Casaseca-de-la-Higuera} } @article {tristan2010dwi, title = {DWI filtering using joint information for DTI and HARDI}, journal = {Medical Image Analysis}, volume = {14}, number = {2}, year = {2010}, pages = {205{\textendash}218}, publisher = {Elsevier}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @article {cardenes2010fast, title = {Fast and accurate geodesic distance transform by ordered propagation}, journal = {Image and Vision Computing}, volume = {28}, number = {3}, year = {2010}, pages = {307{\textendash}316}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @conference {merino2010multiphase, title = {Multiphase level set algorithm for coupled segmentation of multiple regions. Application to MRI segmentation}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE}, year = {2010}, pages = {5042{\textendash}5045}, publisher = {IEEE}, organization = {IEEE}, author = {S. Merino-Caviedes and P{\'e}rez, Mar{\'\i}a Teresa and Marcos Martin-Fernandez} } @conference {garcia2010nurbs, title = {NURBS for the geometrical modeling of a new family of Compact-Supported Radial Basis Functions for elastic registration of medical images}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE}, year = {2010}, pages = {5947{\textendash}5950}, publisher = {IEEE}, organization = {IEEE}, author = {Ver{\'o}nica Garc{\'\i}a-P{\'e}rez and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @inbook {vegas2010probabilistic, title = {Probabilistic-driven oriented speckle reducing anisotropic diffusion with application to cardiac ultrasonic images}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2010}, year = {2010}, pages = {518{\textendash}525}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Frangi, Alejandro F and Cesar Palencia} } @article {cardenes2010saturn, title = {Saturn: A software application of tensor utilities for research in neuroimaging}, journal = {Computer methods and programs in biomedicine}, volume = {97}, number = {3}, year = {2010}, pages = {264{\textendash}279}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Antonio Trist{\'a}n-Vega and Marcos Martin-Fernandez} } @conference {aja2010soft, title = {Soft thresholding for medical image segmentation}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE}, year = {2010}, pages = {4752{\textendash}4755}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Fernandez, Martin} } @proceedings {aja2010statistical, title = {Statistical noise model in GRAPPA-reconstructed images}, year = {2010}, pages = {3859}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and W Scott Hoge} } @conference {de2010tractography, title = {Tractography clustering for fiber selection in ROI-based diffusion tensor studies}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE}, year = {2010}, pages = {5665{\textendash}5668}, publisher = {IEEE}, organization = {IEEE}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @conference {vegas2010influence, title = {On the influence of interpolation on probabilistic models for ultrasonic images}, booktitle = {Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on}, year = {2010}, pages = {292{\textendash}295}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Diego Mart{\'\i}n-Mart{\'\i}nez and Santiago Aja-Fern{\'a}ndez and Cesar Palencia} } @article {tristan2010new, title = {A new methodology for the estimation of fiber populations in the white matter of the brain with the Funk{\textendash}Radon transform}, journal = {NeuroImage}, volume = {49}, number = {2}, year = {2010}, pages = {1301{\textendash}1315}, publisher = {Academic Press}, author = {Antonio Trist{\'a}n-Vega and Carl-Fredik Westin and Santiago Aja-Fern{\'a}ndez} } @conference {merino2010variationally, title = {A variationally based weighted re-initialization method for geometric active contours}, booktitle = {Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on}, year = {2010}, pages = {908{\textendash}911}, publisher = {IEEE}, organization = {IEEE}, author = {S. Merino-Caviedes and Gonzalo Vegas-S{\'a}nchez-Ferrero and P{\'e}rez, M Teresa and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez} } @article {garcia20093, title = {A 3-D collision handling algorithm for surgery simulation based on feedback fuzzy logic}, journal = {Information Technology in Biomedicine, IEEE Transactions on}, volume = {13}, number = {4}, year = {2009}, pages = {451{\textendash}457}, publisher = {IEEE}, author = {Ver{\'o}nica Garc{\'\i}a-P{\'e}rez and Emma Mu{\~n}oz-Moreno and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {garmendia2009acute, title = {Acute myocardial infarction circadian rhythm in a geriatric population in Castilla y Leon}, journal = {Journal of the American Geriatrics Society}, volume = {57}, number = {7}, year = {2009}, pages = {1312{\textendash}1313}, publisher = {Wiley Online Library}, author = {Jose Ramon Garmendia-Leiza and Jesus Maria Andres-de-Llano and Julio Ardura-Fernández and Juan Bautista Lopez-Messa and MD Aguilar-Garcia and Carlos Alberola-Lopez} } @article {martin2009addendum, title = {Addendum to {\textquotedblleft}Sequential anisotropic multichannel Wiener filtering with Rician bias correction applied to 3D regularization of DWI data{\textquotedblright}[Medical Image Analysis 13 (2009) 19{\textendash}35]}, journal = {Medical image analysis}, volume = {13}, number = {6}, year = {2009}, pages = {910}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and J-P Thiran and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {martin2009automatic, title = {Automatic articulated registration of hand radiographs}, journal = {Image and Vision Computing}, volume = {27}, number = {8}, year = {2009}, pages = {1207{\textendash}1222}, publisher = {Elsevier}, author = {Miguel Angel Martin-Fernandez and Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Rodrigo de Luis-Garc{\'\i}a and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {aja2009automatic, title = {Automatic noise estimation in images using local statistics. Additive and multiplicative cases}, journal = {Image and Vision Computing}, volume = {27}, number = {6}, year = {2009}, pages = {756{\textendash}770}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {478, title = {Automatic segmentation of white matter structures from DTI using tensor invariants and tensor orientation}, booktitle = {Proc. Intl. Soc. Mag. Reson. Med}, year = {2009}, author = {Rodrigo de Luis-Garc{\'\i}a and Lopez, C Alberola and Kindlmann, G and Carl-Fredik Westin} } @inbook {tristan2009bias, title = {Bias of least squares approaches for diffusion tensor estimation from array coils in DT{\textendash}MRI}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {919{\textendash}926}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Antonio Trist{\'a}n-Vega and Carl-Fredik Westin and Santiago Aja-Fern{\'a}ndez} } @inbook {tristan2009blurring, title = {On the Blurring of the Funk{\textendash}Radon Transform in Q{\textendash}Ball Imaging}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {415{\textendash}422}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin} } @inbook {cardenes2009characterization, title = {Characterization of anatomic fiber bundles for diffusion tensor image analysis}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {903{\textendash}910}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Daniel Argibay-Qui{\~n}ones and Emma Mu{\~n}oz-Moreno and Marcos Martin-Fernandez} } @article {munoz2009characterization, title = {Characterization of the similarity between diffusion tensors for image registration}, journal = {Computers in biology and medicine}, volume = {39}, number = {3}, year = {2009}, pages = {251{\textendash}265}, publisher = {Pergamon}, author = {Emma Mu{\~n}oz-Moreno and Marcos Martin-Fernandez} } @inbook {tristan2009design, title = {Design and construction of a realistic DWI phantom for filtering performance assessment}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {951{\textendash}958}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @article {tristan2009estimation, title = {Estimation of fiber orientation probability density functions in high angular resolution diffusion imaging}, journal = {NeuroImage}, volume = {47}, number = {2}, year = {2009}, pages = {638{\textendash}650}, publisher = {Elsevier}, author = {Antonio Trist{\'a}n-Vega and Carl-Fredik Westin and Santiago Aja-Fern{\'a}ndez} } @article {aja2009noise, title = {Noise estimation in single-and multiple-coil magnetic resonance data based on statistical models}, journal = {Magnetic resonance imaging}, volume = {27}, number = {10}, year = {2009}, pages = {1397{\textendash}1409}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Carlos Alberola-Lopez} } @article {krissian2009noise, title = {Noise-driven anisotropic diffusion filtering of MRI}, journal = {Image Processing, IEEE Transactions on}, volume = {18}, number = {10}, year = {2009}, pages = {2265{\textendash}2274}, publisher = {IEEE}, author = {K Krissian and Santiago Aja-Fern{\'a}ndez} } @inbook {munoz2009quality, title = {Quality Assessment of Tensor Images}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {79{\textendash}103}, publisher = {Springer London}, organization = {Springer London}, author = {Emma Mu{\~n}oz-Moreno and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez} } @inbook {munoz2009review, title = {Review of techniques for registration of diffusion tensor imaging}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {273{\textendash}297}, publisher = {Springer London}, organization = {Springer London}, author = {Emma Mu{\~n}oz-Moreno and Rub{\'e}n C{\'a}rdenes-Almeida and Marcos Martin-Fernandez} } @inbook {de2009segmentation, title = {Segmentation of tensor fields: Recent advances and perspectives}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {35{\textendash}58}, publisher = {Springer}, organization = {Springer}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez and Carl-Fredik Westin} } @article {martin2009sequential, title = {Sequential anisotropic multichannel Wiener filtering with Rician bias correction applied to 3D regularization of DWI data}, journal = {Medical image analysis}, volume = {13}, number = {1}, year = {2009}, pages = {19{\textendash}35}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and J-P Thiran and Carl-Fredik Westin and Carlos Alberola-Lopez} } @inbook {brun2009similar, title = {Similar Tensor Arrays{\textendash}A Framework for Storage of Tensor Array Data}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {407{\textendash}428}, publisher = {Springer London}, organization = {Springer London}, author = {Brun, Anders and Marcos Martin-Fernandez and Acar, Burak and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and Sigfridsson, Andreas and Dario Sosa-Cabrera and Svensson, Bj{\"o}rn and Herberthson, Magnus and Knutsson, Hans} } @book {aja2009tensors, title = {Tensors in image processing and computer vision}, year = {2009}, publisher = {Springer}, organization = {Springer}, author = {Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a and Tao, Dacheng and Li, Xuelong} } @inbook {merino2009user, title = {User Interfaces to Interact with Tensor Fields}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {429{\textendash}454}, publisher = {Springer London}, organization = {Springer London}, author = {S. Merino-Caviedes and Marcos Martin-Fernandez} } @inbook {martin2009log, title = {A log-euclidean polyaffine registration for articulated structures in medical images}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {156{\textendash}164}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Miguel Angel Martin-Fernandez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {casaseca2009multichannel, title = {A multichannel model-based methodology for extubation readiness decision of patients on weaning trials}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {56}, number = {7}, year = {2009}, pages = {1849{\textendash}1863}, publisher = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {477, title = {A multidimensional segmentation evaluation for medical image data}, journal = {Computer methods and programs in biomedicine}, volume = {96}, year = {2009}, pages = {108{\textendash}124}, abstract = {

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Rodrigo de Luis-Garc{\'\i}a and Bach-Cuadra, Meritxell} } @article {san2008efficient, title = {Efficient tracking of MR tensor fields using a multilayer neural network}, journal = {IAENG International Journal of Computer Science}, volume = {35}, number = {1}, year = {2008}, pages = {129{\textendash}139}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {tristn2008fuzzy, title = {Fuzzy regularisation of deformation fields in image registration}, year = {2008}, pages = {1223{\textendash}30}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @proceedings {san2008ga, title = {A GA-based Approach for Parameter Estimation in DT-MRI Tracking Algorithms}, volume = {1}, year = {2008}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {tristan2008joint, title = {Joint LMMSE estimation of DWI data for DTI processing}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2008}, year = {2008}, pages = {27{\textendash}34}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez} } @conference {tristan2008local, title = {Local similarity measures for demons-like registration algorithms}, booktitle = {Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on}, year = {2008}, pages = {1087{\textendash}1090}, publisher = {IEEE}, organization = {IEEE}, author = {Antonio Trist{\'a}n-Vega and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {aja2008matrix, title = {Matrix modeling of hierarchical fuzzy systems}, journal = {Fuzzy Systems, IEEE Transactions on}, volume = {16}, number = {3}, year = {2008}, pages = {585{\textendash}599}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @proceedings {simmross2008modelling, title = {Modelling Network Traffic as alpha-Stable Stochastic Processes: An Approach Towards Anomaly Detection}, year = {2008}, pages = {25{\textendash}32}, author = {Federico Simmross-Wattenberg and Antonio Trist{\'a}n-Vega and Pablo Casaseca-de-la-Higuera and Juan Ignacio Asensio-P{\'e}rez and Marcos Martin-Fernandez and Yannis A Dimitriadis and Carlos Alberola-Lopez} } @article {aja2008noise, title = {Noise and signal estimation in magnitude MRI and Rician distributed images: a LMMSE approach}, journal = {Image Processing, IEEE Transactions on}, volume = {17}, number = {8}, year = {2008}, pages = {1383{\textendash}1398}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Carl-Fredik Westin} } @article {aja2008restoration, title = {Restoration of DWI data using a Rician LMMSE estimator}, journal = {Medical Imaging, IEEE Transactions on}, volume = {27}, number = {10}, year = {2008}, pages = {1389{\textendash}1403}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Niethammer, Marc and Kubicki, Marek and Martha E Shenton and Carl-Fredik Westin} } @conference {vegas2008strain, title = {Strain Rate Tensor estimation in cine cardiac MRI based on elastic image registration}, booktitle = {Computer Vision and Pattern Recognition Workshops, 2008. CVPRW{\textquoteright}08. IEEE Computer Society Conference on}, year = {2008}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega and Lucilio Cordero-Grande and Pablo Casaseca-de-la-Higuera and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {sosa2008strain, title = {Strain index: a new visualizing parameter for US elastography}, volume = {6920}, year = {2008}, pages = {6920}, publisher = {International Society for Optical Engineering; 1999}, author = {Dario Sosa-Cabrera and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @proceedings {sosa2008strain, title = {Strain index: a new visualizing parameter for US elastography}, year = {2008}, pages = {69200W{\textendash}69200W}, publisher = {International Society for Optics and Photonics}, author = {Dario Sosa-Cabrera and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @article {de2008texture, title = {Texture and color segmentation based on the combined use of the structure tensor and the image components}, journal = {Signal Processing}, volume = {88}, number = {4}, year = {2008}, pages = {776{\textendash}795}, publisher = {Elsevier}, author = {Rodrigo de Luis-Garc{\'\i}a and Deriche, Rachid and Carlos Alberola-Lopez} } @proceedings {433, title = {On the estimation of joint probability density functions for multi-modal registration of medical images}, volume = {26}, year = {2008}, pages = {13-16}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {Valladolid, Spain}, author = {Antonio Trist{\'a}n-Vega and Federico Simmross-Wattenberg and Emma Mu{\~n}oz-Moreno and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez} } @conference {merino2008general, title = {A general interpolation method for symmetric second-rank tensors in two dimensions}, booktitle = {Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on}, year = {2008}, pages = {931{\textendash}934}, publisher = {IEEE}, organization = {IEEE}, author = {S. Merino-Caviedes and Marcos Martin-Fernandez} } @conference {muoz2008methodology, title = {A methodology for quality assessment in tensor images}, booktitle = {Computer Vision and Pattern Recognition Workshops, 2008. CVPRW{\textquoteright}08. IEEE Computer Society Conference on}, year = {2008}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Emma Mu{\~n}oz-Moreno and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez} } @article {422, title = {A radius and ulna TW3 bone age assessment system}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {55}, year = {2008}, pages = {1463-1476}, abstract = {

An end-to-end system to automate the well-known Tanner - Whitehouse (TW3) clinical procedure to estimate the skeletal age in childhood is proposed. The system comprises the detailed analysis of the two most important bones in TW3: the radius and ulna wrist bones. First, a modified version of an adaptive clustering segmentation algorithm is presented to properly semi-automatically segment the contour of the bones. Second, up to 89 features are defined and extracted from bone contours and gray scale information inside the contour, followed by some well-founded feature selection mathematical criteria, based on the ideas of maximizing the classes{\textquoteright} separability. Third, bone age is estimated with the help of a Generalized Softmax Perceptron (GSP) neural network (NN) that, after supervised learning and optimal complexity estimation via the application of the recently developed Posterior Probability Model Selection (PPMS) algorithm, is able to accurately predict the different development stages in both radius and ulna from which and with the help of the TW3 methodology, we are able to conveniently score and estimate the bone age of a patient in years, in what can be understood as a multiple-class (multiple stages) pattern recognition approach with posterior probability estimation. Finally, numerical results are presented to evaluate the system performance in predicting the bone stages and the final patient bone age over a private hand image database, with the help of the pediatricians and the radiologists expert diagnoses. {\^A}{\textcopyright} 2006 IEEE.

}, keywords = {Age Determination by Skeleton, Aging, Algorithms, Artificial Intelligence, Automated, Bone, Bone age assessment, Clustering algorithms, Computer-Assisted, Humans, Model selection, Neural networks, Pattern recognition, Radiographic Image Interpretation, Reproducibility of Results, Sensitivity and Specificity, Skeletal maturity, algorithm, article, artificial neural network, automation, bone age, bone maturation, childhood, instrumentation, radius, ulna}, issn = {00189294}, doi = {10.1109/TBME.2008.918554}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-42249094547\&partnerID=40\&md5=2cecfea5f75a61b048611f2391b00aed}, author = {Antonio Trist{\'a}n-Vega and J I Arribas} } @proceedings {aja2008unbiased, title = {An unbiased Non-Local Means scheme for DWI filtering}, year = {2008}, pages = {277{\textendash}284}, author = {Santiago Aja-Fern{\'a}ndez and K Krissian} } @conference {de2007p6d, title = {Analysis of Ultrasound Images Based on Local Statistics. Application to the Diagnosis of Developmental Dysplasia of the Hip}, booktitle = {Ultrasonics Symposium, 2007. IEEE}, year = {2007}, pages = {2531{\textendash}2534}, publisher = {IEEE}, organization = {IEEE}, author = {Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Rub{\'e}n C{\'a}rdenes-Almeida and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {aksoy2007dti, title = {DTI Application with Haptic Interfaces}, volume = {7}, year = {2007}, pages = {1{\textendash}9}, author = {Aksoy, Murat and Avcu, Neslehan and S. Merino-Caviedes and Diktas, Engin Deniz and Miguel Angel Martin-Fernandez and Girgin, S{\i}la and Marras, Ioannis and Emma Mu{\~n}oz-Moreno and Tekeli, Erkin and Acar, Burak} } @proceedings {luis2007general, title = {General Medical Image Computing{\textendash}I-Mixtures of Gaussians on Tensor Fields for DT-MRI Segmentation}, volume = {4791}, year = {2007}, pages = {319{\textendash}326}, publisher = {Berlin: Springer-Verlag, 1973-}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @inbook {de2007mixtures, title = {Mixtures of gaussians on tensor fields for DT-MRI segmentation}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2007}, year = {2007}, pages = {319{\textendash}326}, publisher = {Springer}, organization = {Springer}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @conference {480, title = {Multimodal evaluation for medical image segmentation}, booktitle = {Computer Analysis of Images and Patterns}, year = {2007}, publisher = {Springer}, organization = {Springer}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Bach, Meritxell and Chi, Ying and Marras, Ioannis and Rodrigo de Luis-Garc{\'\i}a and Anderson, Mats and Cashman, Peter and Bultelle, Matthieu} } @conference {san2007neural, title = {Neural Network-Assisted Fiber Tracking of Synthetic and White Matter DT-MR Images.}, booktitle = {World Congress on Engineering}, year = {2007}, pages = {618{\textendash}623}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {niethammer2007outlier, title = {Outlier rejection for diffusion weighted imaging}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2007}, year = {2007}, pages = {161{\textendash}168}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Niethammer, Marc and Bouix, Sylvain and Santiago Aja-Fern{\'a}ndez and Carl-Fredik Westin and Martha E Shenton} } @conference {martin2007parameter, title = {Parameter Estimation of the Homodyned K Distribution Based on Signal to Noise Ratio}, booktitle = {Ultrasonics Symposium, 2007. IEEE}, year = {2007}, pages = {158{\textendash}161}, publisher = {IEEE}, organization = {IEEE}, author = {Marcos Martin-Fernandez and Rub{\'e}n C{\'a}rdenes-Almeida and Carlos Alberola-Lopez} } @article {martin2007sequential, title = {Sequential anisotropic Wiener filtering applied to 3D MRI data}, journal = {Magnetic resonance imaging}, volume = {25}, number = {2}, year = {2007}, pages = {278{\textendash}292}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez and Juan Ruiz-Alzola and Carl-Fredik Westin} } @inbook {aja2007signal, title = {Signal LMMSE estimation from multiple samples in MRI and DT-MRI}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2007}, year = {2007}, pages = {368{\textendash}375}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Carl-Fredik Westin} } @article {martin2007techniques, title = {Techniques in the contour detection of kidneys and their applications}, journal = {World Scientific Publishing Company}, year = {2007}, pages = {381{\textendash}398}, author = {Marcos Martin-Fernandez and Lucilio Cordero-Grande and Emma Mu{\~n}oz-Moreno and Carlos Alberola-Lopez} } @conference {aja2007tissue, title = {Tissue identification in ultrasound images using rayleigh local parameter estimation}, booktitle = {Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on}, year = {2007}, pages = {1129{\textendash}1133}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {479, title = {Ultrasound Based Intraoperative Brain Shift Correction}, booktitle = {Ultrasonics Symposium, 2007. IEEE}, year = {2007}, publisher = {IEEE}, organization = {IEEE}, author = {Gonz{\'a}lez, Javier and Dario Sosa-Cabrera and Ortega, Mario and Gil, Jose Antonio and Antonio Trist{\'a}n-Vega and Emma Mu{\~n}oz-Moreno and Rodrigo de Luis-Garc{\'\i}a} } @proceedings {cardenes2007usimagtool, title = {Usimagtool: an open source freeware software for ultrasound imaging and elastography}, year = {2007}, pages = {117{\textendash}127}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Antonio Trist{\'a}n-Vega and Ferrero, GVS and Santiago Aja-Fern{\'a}ndez} } @article {bouix2007evaluating, title = {On evaluating brain tissue classifiers without a ground truth}, journal = {Neuroimage}, volume = {36}, number = {4}, year = {2007}, pages = {1207{\textendash}1224}, publisher = {Academic Press}, author = {Bouix, Sylvain and Marcos Martin-Fernandez and Ungar, Lida and Nakamura, Motoaki and Koo, Min-Seong and McCarley, Robert W and Martha E Shenton} } @article {419, title = {A fast B-spline pseudo-inversion algorithm for consistent image registration}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {4673 LNCS}, year = {2007}, pages = {768-775}, abstract = {

Recently, the concept of consistent image registration has been introduced to refer to a set of algorithms that estimate both the direct and inverse deformation together, that is, they exchange the roles of the target and the scene images alternatively; it has been demonstrated that this technique improves the registration accuracy, and that the biological significance of the obtained deformations is also improved. When dealing with free form deformations, the inversion of the transformations obtained becomes computationally intensive. In this paper, we suggest the parametrization of such deformations by means of a cubic B-spline, and its approximated inversion using a highly efficient algorithm. The results show that the consistency constraint notably improves the registration accuracy, especially in cases of a heavy initial misregistration, with very little computational overload. {\^A}{\textcopyright} Springer-Verlag Berlin Heidelberg 2007.

}, keywords = {Approximation algorithms, Computational overload, Consistent registration, Constraint theory, Image registration, Inverse problems, Inverse transformation, Parameterization}, isbn = {9783540742715}, issn = {03029743}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-38149022572\&partnerID=40\&md5=627751cd7654872cbd9ee74a249752eb}, author = {Antonio Trist{\'a}n-Vega and J I Arribas} } @conference {san2007new, title = {A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images}, booktitle = {Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on}, year = {2007}, pages = {1{\textendash}4}, publisher = {IEEE}, organization = {IEEE}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {418, title = {A statistical-genetic algorithm to select the most significant features in mammograms}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {4673 LNCS}, year = {2007}, pages = {189-196}, abstract = {

An automatic classification system into either malignant or benign microcalcification from mammograms is a helpful tool in breast cancer diagnosis. From a set of extracted features, a classifying method using neural networks can provide a probability estimation that can help the radiologist in his diagnosis. With this objective in mind, this paper proposes a feature selection algorithm from a massive number of features based on a statistical distance method in conjunction with a genetic algorithm (GA). The use of a statistical distance as optimality criterion was improved with genetic algorithms for selecting an appropriate subset of features, thus making this algorithm capable of performing feature selection from a massive set of initial features. Additionally, it provides a criterion to select an appropriate number of features to be employed. Experimental work was performed using Generalized Softmax Perceptrons (GSP), trained with a Strict Sense Bayesian cost function for direct probability estimation, as microcalcification classifiers. A Posterior Probability Model Selection (PPMS) algorithm was employed to determine the network complexity. Results showed that this algorithm converges into a subset of features which has a good classification rate and Area Under Curve (AUC) of the Receiver Operating Curve (ROC). {\^A}{\textcopyright} Springer-Verlag Berlin Heidelberg 2007.

}, keywords = {Breast cancer, Diagnosis, Feature extraction, Genetic algorithms, Mammography, Microcalcification classification, Network complexity, Neural network classifiers, Neural networks, Tumors}, isbn = {9783540742715}, issn = {03029743}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-38149142403\&partnerID=40\&md5=ef139db3a0e5d603c4f721316abdcf2c}, author = {G V Sanchez-Ferrero and J I Arribas} } @conference {cordero2006endocardium, title = {Endocardium and epicardium contour modeling based on Markov random fields and active contours}, booktitle = {Engineering in Medicine and Biology Society, 2006. EMBS{\textquoteright}06. 28th Annual International Conference of the IEEE}, year = {2006}, pages = {928{\textendash}931}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {421, title = {Estimation of Posterior Probabilities with Neural Networks: Application to Microcalcification Detection in Breast Cancer Diagnosis}, booktitle = {Handbook of Neural Engineering}, year = {2006}, pages = {41-58}, publisher = {John Wiley \& Sons, Inc.}, organization = {John Wiley \& Sons, Inc.}, isbn = {9780470056691}, doi = {10.1002/9780470068298.ch3}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-42249107409\&partnerID=40\&md5=aac6237961cec1a48c0e843a9a1912a4}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and Carlos Alberola-Lopez} } @article {aja2006fuzzy, title = {Fuzzy feedback system analysis using transition matrices}, journal = {Fuzzy sets and systems}, volume = {157}, number = {4}, year = {2006}, pages = {516{\textendash}543}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @proceedings {aja2006image, title = {Image quality assessment based on local variance}, year = {2006}, pages = {4815{\textendash}4818}, author = {Santiago Aja-Fern{\'a}ndez and Raul San Jose-Estepar and Carlos Alberola-Lopez and Carl-Fredik Westin} } @conference {de2006parametric, title = {Parametric 3D hip joint segmentation for the diagnosis of developmental dysplasia}, booktitle = {Engineering in Medicine and Biology Society, 2006. EMBS{\textquoteright}06. 28th Annual International Conference of the IEEE}, year = {2006}, pages = {4807{\textendash}4810}, publisher = {IEEE}, organization = {IEEE}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @conference {martin2006speckle, title = {A Speckle Removal Filter Based on Anisotropic Wiener Filtering and the Rice Distribution}, booktitle = {Ultrasonics Symposium, 2006. IEEE}, year = {2006}, pages = {1694{\textendash}1697}, publisher = {IEEE}, organization = {IEEE}, author = {Marcos Martin-Fernandez and Emma Mu{\~n}oz-Moreno and Carlos Alberola-Lopez} } @inbook {westin2006tensor, title = {Tensor field regularization using normalized convolution and markov random fields in a bayesian framework}, booktitle = {Visualization and Processing of Tensor Fields}, year = {2006}, pages = {381{\textendash}398}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Carl-Fredik Westin and Marcos Martin-Fernandez and Carlos Alberola-Lopez and Juan Ruiz-Alzola and Knutsson, Hans} } @article {casaseca2006weaning, title = {Weaning from mechanical ventilation: a retrospective analysis leading to a multimodal perspective}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {53}, number = {7}, year = {2006}, pages = {1330{\textendash}1345}, publisher = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {aja2006estimation, title = {On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering}, journal = {Image Processing, IEEE Transactions on}, volume = {15}, number = {9}, year = {2006}, pages = {2694{\textendash}2701}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @proceedings {san2006new, title = {A new method for fiber tractography in diffusion tensor magnetic resonance images}, volume = {6}, year = {2006}, pages = {380{\textendash}385}, author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {lopez2005age, title = {Age as modifying factor of circadian rhythm of acute myocardial infarction}, journal = {MEDICINA INTENSIVA}, volume = {29}, number = {9}, year = {2005}, pages = {455}, publisher = {IDEPSA}, author = {Juan Bautista Lopez-Messa and JR Garmendia-Leiza and MD Aguilar-Garcia and Jes{\'u}s Mar{\'\i}a And De Llano and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @conference {martin2005articulated, title = {Articulated registration: Elastic registration based on a wire-model}, booktitle = {Medical Imaging}, year = {2005}, pages = {182{\textendash}191}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Miguel Angel Martin-Fernandez and Emma Mu{\~n}oz-Moreno and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {arribas2005estimation, title = {Estimation of Posterior Probabilities with Neural Networks: Application to Microcalcification Detection in Breast Cancer Diagnosis}, booktitle = {Handbook of Neural Engineering}, year = {2005}, pages = {41{\textendash}58}, publisher = {Wiley Online Library}, organization = {Wiley Online Library}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and Carlos Alberola-Lopez} } @article {aja2005fast, title = {Fast inference using transition matrices: An extension to nonlinear operators}, journal = {Fuzzy Systems, IEEE Transactions on}, volume = {13}, number = {4}, year = {2005}, pages = {478{\textendash}490}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {palacios2005group, title = {Group-Slicer: A collaborative extension of 3D-Slicer}, journal = {Journal of Biomedical Informatics}, volume = {38}, year = {2005}, pages = {431{\textendash}442}, author = {Federico Simmross-Wattenberg and Palacios-Camarero, Cristina and Pablo Casaseca-de-la-Higuera and Miguel Angel Martin-Fernandez and Santiago Aja-Fern{\'a}ndez and Juan Ruiz-Alzola and Carl-Fredik Westin and Carlos Alberola-Lopez} } @conference {de2005hip, title = {Hip joint segmentation from 2D ultrasound data based on dynamic shape priors}, booktitle = {Proceedings of the 4th WSEAS international conference on Electronics, control and signal processing}, year = {2005}, pages = {245{\textendash}250}, publisher = {World Scientific and Engineering Academy and Society (WSEAS)}, organization = {World Scientific and Engineering Academy and Society (WSEAS)}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @article {munoz2005image, title = {Image registration based on automatic detection of anatomical landmarks for bone age assessment}, journal = {WSEAS Transactions on Computers}, volume = {4}, number = {11}, year = {2005}, pages = {1596{\textendash}1603}, author = {Emma Mu{\~n}oz-Moreno and Rub{\'e}n C{\'a}rdenes-Almeida and Rodrigo de Luis-Garc{\'\i}a and Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez} } @article {ruiz2005kriging, title = {Kriging filters for multidimensional signal processing}, journal = {Signal Processing}, volume = {85}, number = {2}, year = {2005}, pages = {413{\textendash}439}, publisher = {Elsevier}, author = {Juan Ruiz-Alzola and Carlos Alberola-Lopez and Carl-Fredik Westin} } @article {lopez2005edad, title = {La edad como factor modificador del ritmo circadiano del infarto agudo de miocardio}, journal = {Medicina intensiva}, volume = {29}, number = {9}, year = {2005}, pages = {455{\textendash}461}, publisher = {Elsevier}, author = {Juan Bautista Lopez-Messa and JR Garmendia-Leiza and MD Aguilar-Garcia and Jes{\'u}s Mar{\'\i}a And De Llano and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @inbook {ruiz2005landmark, title = {Landmark-Based Registration of Medical-Image Data}, booktitle = {Medical Image Analysis Methods, Edited by Lena Costaridou, CRC Press}, year = {2005}, author = {Juan Ruiz-Alzola and Suarez-Santana, E and Carlos Alberola-Lopez and Carl-Fredik Westin} } @conference {aja2005matrix, title = {Matrix Inference in Fuzzy Decision Trees.}, booktitle = {EUSFLAT Conf.}, year = {2005}, pages = {979{\textendash}984}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {luis2005poster, title = {Poster Presentations 2-Pattern Recognition, Image Processing, and Applications-Tensor Processing for Texture and Colour Segmentation}, journal = {Lecture Notes in Computer Science}, volume = {3540}, year = {2005}, pages = {1117{\textendash}1127}, publisher = {Berlin: Springer-Verlag, 1973-}, author = {Rodrigo de Luis-Garc{\'\i}a and Deriche, Rachid and Rousson, Mikael and Carlos Alberola-Lopez} } @conference {de2005pull, title = {Pull-Push Level Sets: A new term to encode prior knowledge for the segmentation of teeth images}, booktitle = {Medical Imaging}, year = {2005}, pages = {598{\textendash}605}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Rodrigo de Luis-Garc{\'\i}a and Raul San Jose-Estepar and Carlos Alberola-Lopez} } @inbook {de2005tensor, title = {Tensor processing for texture and colour segmentation}, booktitle = {Image Analysis}, year = {2005}, pages = {1117{\textendash}1127}, publisher = {Springer}, organization = {Springer}, author = {Rodrigo de Luis-Garc{\'\i}a and Deriche, Rachid and Rousson, Mikael and Carlos Alberola-Lopez} } @inbook {martin2005two, title = {Two methods for validating brain tissue classifiers}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2005}, year = {2005}, pages = {515{\textendash}522}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Marcos Martin-Fernandez and Bouix, Sylvain and Ungar, Lida and McCarley, Robert W and Martha E Shenton} } @conference {429, title = {Weaning from mechanical ventilation: feature extraction from a statistical signal processing viewpoint}, booktitle = {Proc. 13th Signal Processing Conf., EUSIPCO}, year = {2005}, author = {Pablo Casaseca-de-la-Higuera and Rodrigo de Luis-Garc{\'\i}a and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @article {martin2005approach, title = {An approach for contour detection of human kidneys from ultrasound images using Markov random fields and active contours}, journal = {Medical Image Analysis}, volume = {9}, number = {1}, year = {2005}, pages = {1{\textendash}23}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {casaseca2006comparative, title = {A comparative study on microcalcification detection methods with posterior probability estimation based on Gaussian mixture models}, year = {2005}, pages = {49{\textendash}54}, publisher = {IEEE}, abstract = {Automatic detection of microcalcifications in mammograms constitutes a helpful tool in breast cancer diagnosis. Radiologist{\textquoteright}s confidence level on microcalcification detection would be improved if a probability estimate of its presence could be obtained from computer-aided diagnosis. In this paper we explore detection performance of a simple Bayesian classifier based on Gaussian mixture probability density functions (pdf). Posterior probability of microcalcification presence may be estimated from the probabilistic model. Two model selection algorithms have been tested, one based on the minimum message length criterion and the other on discriminative criteria obtained from the classifier performance. In addition, we propose a complementing model selection algorithm in order to improve the initial system performance obtained with these methods. Simulation results show that our model gets a good compromise between classification performance and probability estimation accuracy}, doi = {https://doi.org/10.1109/IEMBS.2005.1616339}, url = {https://ieeexplore.ieee.org/abstract/document/1616339}, author = {Pablo Casaseca-de-la-Higuera and J I Arribas and Emma Mu{\~n}oz-Moreno and Carlos Alberola L{\'o}pez} } @conference {430, title = {A lossless compression algorithm based on predictive coding for volumetric medical datasets}, booktitle = {Proc. EUSIPCO 2005}, year = {2005}, author = {D{\'\i}ez-Garc{\'\i}a, M{\'o}nica and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @article {martín2005low, title = {On low order moments of the homodyned-k distribution}, journal = {Ultrasonics}, volume = {43}, number = {4}, year = {2005}, pages = {283{\textendash}290}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {420, title = {A model selection algorithm for a posteriori probability estimation with neural networks}, journal = {IEEE Transactions on Neural Networks}, volume = {16}, year = {2005}, pages = {799-809}, abstract = {

This paper proposes a novel algorithm to jointly determine the structure and the parameters of a posteriori probability model based on neural networks (NNs). It makes use of well-known ideas of pruning, splitting, and merging neural components and takes advantage of the probabilistic interpretation of these components. The algorithm, so called a posteriori probability model selection (PPMS), is applied to an NN architecture called the generalized softmax perceptron (GSP) whose outputs can be understood as probabilities although results shown can be extended to more general network architectures. Learning rules are derived from the application of the expectation-maximization algorithm to the GSP-PPMS structure. Simulation results show the advantages of the proposed algorithm with respect to other schemes. {\^A}{\textcopyright} 2005 IEEE.

}, keywords = {Algorithms, Automated, Biological, Breast Neoplasms, Computer simulation, Computer-Assisted, Computing Methodologies, Decision Support Techniques, Diagnosis, Estimation, Expectation-maximization, Generalized Softmax Perceptron (GSP), Humans, Mathematical models, Model selection, Models, Neural Networks (Computer), Neural networks, Numerical Analysis, Objective function, Pattern recognition, Posterior probability, Probability, Statistical, Stochastic Processes, algorithm, article, artificial neural network, automated pattern recognition, biological model, breast tumor, classification, cluster analysis, computer analysis, computer assisted diagnosis, decision support system, evaluation, human, mathematical computing, methodology, statistical model, statistics}, issn = {10459227}, doi = {10.1109/TNN.2005.849826}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-23044459586\&partnerID=40\&md5=f00e7d86a625cfc466373a2a938276d0}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro} } @conference {428, title = {The opportunity of grid services for CSCL-application development}, booktitle = {Parallel, Distributed and Network-Based Processing, 2005. PDP 2005. 13th Euromicro Conference on}, year = {2005}, publisher = {IEEE}, organization = {IEEE}, address = {Lausanne, Switzerland}, author = {Vaquero-Gonz{\'a}lez, Luis M and Hern{\'a}ndez-Leo, D and Federico Simmross-Wattenberg and Bote-Lorenzo, Miguel L and Juan Ignacio Asensio-P{\'e}rez and Yannis A Dimitriadis and G{\'o}mez-S{\'a}nchez, Eduardo and Vega-Gorgojo, Guillermo} } @conference {417, title = {A radius and ulna skeletal age assessment system}, booktitle = {2005 IEEE Workshop on Machine Learning for Signal Processing}, year = {2005}, address = {Mystic, CT}, abstract = {

An end to end system to partially automate the TW3 bone age assessment procedure is proposed. The system comprises the detailed analysis of the two more important bones in TW3: the radius and ulna wrist bones. First, a generalization of K-means algorithm is presented to semi-automatically segment the contour of the bones and thus extract up to 89 features describing shapes and textures from bones. Second, a well-founded feature selection criterion based on the statistical properties of data is used in order to properly choose the most relevant features. Third, bone age is estimated with the help of a Generalized Softmax Perceptron (GSP) Neural Network (NN) whose optimal complexity is estimated via the Posterior Probability Model Selection (PPMS) algorithm. We can then predict the different development stages in both radius and ulna, from which we are able to score and estimate the bone age of a patient in years and finally we compare the NN results with those from the pediatrician expert discrepancies. {\^A}{\textcopyright} 2005 IEEE.

}, keywords = {Algorithms, Bone, Feature extraction, Generalized Softmax Perceptron (GSP), Living systems studies, Neural networks, Probability Model Selection (PPMS), Skeletal age assessment system}, isbn = {0780395174; 9780780395176}, doi = {10.1109/MLSP.2005.1532903}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-33749052083\&partnerID=40\&md5=eefa29ac09f4efa304b613cf07ab8d10}, author = {Antonio Trist{\'a}n-Vega and J I Arribas} } @inbook {martin20043d, title = {3D Bayesian regularization of diffusion tensor MRI using multivariate Gaussian Markov random fields}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2004}, year = {2004}, pages = {351{\textendash}359}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Marcos Martin-Fernandez and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {lopez2004cardiovascular, title = {Cardiovascular risk factors in the circadian rhythm of acute myocardial infarction}, journal = {Revista Espa{\~n}ola de Cardiolog{\'\i}a (English Edition)}, volume = {57}, number = {9}, year = {2004}, pages = {850{\textendash}858}, publisher = {Elsevier}, author = {L{\'o}pez Messa, Juan B and JR Garmendia-Leiza and Aguilar Garc{\'\i}a, Mar{\'\i}a D and Jes{\'u}s Mar{\'\i}a And De Llano and Alberola L{\'o}pez, Carlos and Fern{\'a}ndez, Julio Ardura} } @article {alberola2004comments, title = {Comments on: A methodology for evaluation of boundary detection algorithms on medical images}, journal = {Medical Imaging, IEEE Transactions on}, volume = {23}, number = {5}, year = {2004}, pages = {658{\textendash}660}, publisher = {IEEE}, author = {Carlos Alberola-Lopez and Marcos Martin-Fernandez and Juan Ruiz-Alzola} } @article {garmendia2004diferencias, title = {Diferencias en el ritmo circadiano del infarto de miocardio seg{\'u}n su extensi{\'o}n electrocardiogr{\'a}fica}, journal = {Medicina clinica}, volume = {123}, number = {17}, year = {2004}, pages = {641{\textendash}645}, publisher = {Elsevier Doyma}, author = {Jose Ramon Garmendia-Leiza and Juan Bautista Lopez-Messa and Jesus Maria Andres-de-Llano and Carlos Alberola-Lopez and Julio Ardura-Fernández} } @article {garmendia2004differential, title = {Differential circadian rhythms in myocardial infarction according to its extent by electrocardiogram}, journal = {Medicina clinica}, volume = {123}, number = {17}, year = {2004}, pages = {641{\textendash}646}, author = {Jose Ramon Garmendia-Leiza and Juan Bautista Lopez-Messa and Jesus Maria Andres-de-Llano and Carlos Alberola-Lopez and Julio Ardura-Fernández} } @article {lopez2004factores, title = {Factores de riesgo cardiovascular en el ritmo circadiano del infarto agudo de miocardio}, journal = {Revista Espa{\~n}ola de Cardiolog{\'\i}a (English Edition)}, volume = {57}, number = {9}, year = {2004}, pages = {850{\textendash}858}, publisher = {Elsevier}, author = {L{\'o}pez Messa, Juan B and JR Garmendia-Leiza and Aguilar Garc{\'\i}a, Mar{\'\i}a D and Jes{\'u}s Mar{\'\i}a And De Llano and Alberola L{\'o}pez, Carlos and Ardura Fern{\'a}ndez, Julio} } @article {aja2004fast, title = {Fast inference in SAM fuzzy systems using transition matrices}, journal = {Fuzzy Systems, IEEE Transactions on}, volume = {12}, number = {2}, year = {2004}, pages = {170{\textendash}182}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {aja2004fuzzy, title = {Fuzzy Granules as a Basic Word Representation for Computing with Words}, booktitle = {9th Conference Speech and Computer}, year = {2004}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {aja2004hierarchical, title = {Hierarchical fuzzy systems with FITM}, booktitle = {Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on}, volume = {2}, year = {2004}, pages = {767{\textendash}772}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {415, title = {Neural network fusion strategies for identifying breast masses}, booktitle = {IEEE International Conference on Neural Networks - Conference Proceedings}, year = {2004}, address = {Budapest}, abstract = {

In this work, we introduce the Perceptron Average neural network fusion strategy and implemented a number of other fusion strategies to identify breast masses in mammograms as malignant or benign with both balanced and imbalanced input features. We numerically compare various fixed and trained fusion rules, i.e., the Majority Vote, Simple Average, Weighted Average, and Perceptron Average, when applying them to a binary statistical pattern recognition problem. To judge from the experimental results, the Weighted Average approach outperforms the other fusion strategies with balanced input features, while the Perceptron Average is superior and achieves the goals with lowest standard deviation with imbalanced ensembles. We concretely analyze the results of above fusion strategies, state the advantages of fusing the component networks, and provide our particular broad sense perspective about information fusion in neural networks.

}, keywords = {Biological organs, Breast cancers, Component neural networks (CNN), Image segmentation, Information fusions, Learning algorithms, Linear systems, Mammography, Mathematical models, Multilayer neural networks, Pattern recognition, Posterior probabilities, Tumors}, isbn = {0780383591}, doi = {10.1109/IJCNN.2004.1381010}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-10844231826\&partnerID=40\&md5=2be794a5832413fed34152d61dd49388}, author = {Y Wu and J He and Y Man and J I Arribas} } @article {aja2004computational, title = {A computational TW3 classifier for skeletal maturity assessment. A Computing with Words approach}, journal = {Journal of Biomedical Informatics}, volume = {37}, number = {2}, year = {2004}, pages = {99{\textendash}107}, publisher = {Academic Press}, author = {Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a and Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez} } @article {tardon2004novel, title = {A novel Markovian formulation of the correspondence problem in stereo vision}, journal = {Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on}, volume = {34}, number = {3}, year = {2004}, pages = {428{\textendash}436}, publisher = {IEEE}, author = {Lorenzo J Tard{\'o}n-Garc{\'\i}a and Javier Portillo-Garcia and Carlos Alberola-Lopez} } @conference {martin2003automatic, title = {Automatic bone age assessment: A registration approach}, booktitle = {Medical Imaging 2003}, year = {2003}, pages = {1765{\textendash}1776}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Miguel Angel Martin-Fernandez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {de2003biometric, title = {Biometric identification systems}, journal = {Signal Processing}, volume = {83}, number = {12}, year = {2003}, pages = {2539{\textendash}2557}, publisher = {Elsevier}, author = {Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez and Aghzout, Otman and Juan Ruiz-Alzola} } @inbook {jose2003lncs, title = {Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution}, booktitle = {Lecture Notes in Computer Science}, volume = {2879}, year = {2003}, pages = {382{\textendash}390}, publisher = {Berlin: Springer-Verlag, 1973-}, organization = {Berlin: Springer-Verlag, 1973-}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Carlos Alberola-Lopez and Ellsmere, James and Kikinis, Ron and Carl-Fredik Westin} } @inbook {jose2003freehand, title = {Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution}, booktitle = {Lecture Notes in Computer Science}, volume = {2879}, year = {2003}, pages = {382{\textendash}390}, publisher = {Berlin: Springer-Verlag, 1973-}, organization = {Berlin: Springer-Verlag, 1973-}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Carlos Alberola-Lopez and Ellsmere, James and Kikinis, Ron and Carl-Fredik Westin} } @conference {413, title = {Fusing Output Information in Neural Networks: Ensemble Performs Better}, booktitle = {Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings}, year = {2003}, address = {Cancun}, abstract = {

A neural network ensemble is a learning paradigm where a finite number of component neural networks are trained for the same task. Previous research suggests that an ensemble as a whole is often more accurate than any of the single component networks. This paper focuses on the advantages of fusing different nature network architectures, and to determine the appropriate information fusion algorithm in component neural networks by several approaches within hard decision classifiers, when solving a binary pattern recognition problem. We numerically simulated and compared the different fusion approaches in terms of the mean-square error rate in testing data set, over synthetically generated binary Gaussian noisy data, and stated the advantages of fusing the hard outputs of different component networks to make a final hard decision classification. The results of the experiments indicate that neural network ensembles can indeed improve the overall accuracy for classification problems; in all fusion architectures tested, the ensemble correct classification rates are better than those achieved by the individual component networks. Finally we are nowadays comparing the above mentioned hard decision classifiers with new soft decision classifier architectures that make use of the additional continuous type intermediate network soft outputs, fulfilling probability fundamental laws (positive, and add to unity), which can be understood as the a posteriori probabilities of a given pattern to belong to a certain class.

}, keywords = {Algorithms, Backpropagation, Classification (of information), Computer simulation, Decision making, Estimation, Gaussian noise (electronic), Information fusions, Mathematical models, Medical imaging, Model selection, Multilayer neural networks, Neural network ensembles, Pattern recognition, Probability, Probability estimation, Problem solving, Regularization, Statistical methods, Statistical pattern recognition, Vectors}, doi = {https://doi.org/10.1109/IEMBS.2003.1280254}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-1542301061\&partnerID=40\&md5=32dbadb3b6ac3c6ae1ea33d89b52c75f}, author = {Y Wu and J I Arribas} } @inbook {ruiz2003geostatistical, title = {Geostatistical medical image registration}, booktitle = {Medical Image Computing and Computer-Assisted Intervention-MICCAI 2003}, year = {2003}, pages = {894{\textendash}901}, publisher = {Springer}, organization = {Springer}, author = {Juan Ruiz-Alzola and Suarez, Eduardo and Carlos Alberola-Lopez and Warfield, Simon K and Carl-Fredik Westin} } @conference {aja2003inference, title = {Inference with fuzzy granules for computing with words: a practical viewpoint}, booktitle = {Fuzzy Systems, 2003. FUZZ{\textquoteright}03. The 12th IEEE International Conference on}, volume = {1}, year = {2003}, pages = {566{\textendash}571}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {arribas2003neural, title = {Neural posterior probabilities for microcalcification detection in breast cancer diagnoses}, booktitle = {Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on}, year = {2003}, pages = {660{\textendash}663}, publisher = {IEEE}, organization = {IEEE}, abstract = {We apply the a Posteriori Probability Model Selection (PPMS) algorithm with the help of Generalized Softmax Perceptron (GSP) neural architecture in order to obtain estimates of the posterior class probabilities at its outputs, in the binary problem of microcalcification detection in a hospital digitalized mammogram database. We first detect windowed images with high probability to belong to the class microcalcification is present, then we locally segment the shape of the calcifications, and finally show the segmented microcalcifications to the radiologist. The segmented images together with the posterior probabilities for each window image can be employed as a valuable information to help predicting a breast diagnosis, in order to distinguish between benignant calcium deposit and malignant accumulation, that is, breast carcinoma.}, doi = {https://doi.org/10.1109/CNE.2003.1196915}, url = {https://ieeexplore.ieee.org/abstract/document/1196915}, author = {J I Arribas and Carlos Alberola L{\'o}pez and Mateos-Marcos, A and Jes{\'u}s Cid-Sueiro} } @inbook {martin2003regularization, title = {Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach}, booktitle = {Lecture Notes in Computer Science}, volume = {2879}, year = {2003}, pages = {92{\textendash}100}, publisher = {Berlin: Springer-Verlag}, organization = {Berlin: Springer-Verlag}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez and Juan Ruiz-Alzola and Carl-Fredik Westin} } @conference {luis2003fully, title = {A fully automatic algorithm for contour detection of bones in hand radiographs using active contours}, booktitle = {Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on}, volume = {3}, year = {2003}, pages = {III{\textendash}421}, publisher = {IEEE}, organization = {IEEE}, abstract = {This paper presents an algorithm for automatically detecting bone contours from hand radiographs using active contours. Prior knowledge is first used to locate initial contours for the snakes inside each bone of interest. Next, an adaptive snake algorithm is applied so that parameters are properly adjusted for each bone specifically. We introduce a novel truncation technique to prevent the external forces of the snake from pulling the contour outside the bones boundaries, yielding excellent results.}, doi = {https://doi.org/10.1109/ICIP.2003.1247271}, url = {https://ieeexplore.ieee.org/abstract/document/1247271}, author = {Rodrigo de Luis-Garc{\'\i}a and Marcos Martin-Fernandez and J I Arribas and Carlos Alberola L{\'o}pez} } @conference {luis2003fully, title = {A fully automatic algorithm for contour detection of bones in hand radiographs using active contours}, booktitle = {Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on}, volume = {3}, year = {2003}, pages = {III{\textendash}421}, publisher = {IEEE}, organization = {IEEE}, author = {Rodrigo de Luis-Garc{\'\i}a and Marcos Martin-Fernandez and J I Arribas and Carlos Alberola-Lopez} } @conference {414, title = {A fully automatic algorithm for contour detection of bones in hand radiographs using active contours}, booktitle = {IEEE International Conference on Image Processing}, year = {2003}, address = {Barcelona}, abstract = {

This paper1 presents an algorithm for automatically detecting bone contours from hand radiographs using active contours. Prior knowledge is first used to locate initial contours for the snakes inside each bone of interest. Next, an adaptive snake algorithm is applied so that parameters are properly adjusted for each bone specifically. We introduce a novel truncation technique to prevent the external forces of the snake from pulling the contour outside the bones boundaries, yielding excelent results.

}, keywords = {Active contours, Algorithms, Bone, Cocentric circumferences, Contour measurement, Medical imaging, Object recognition, Radiography}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0344271749\&partnerID=40\&md5=5fcf06edb482cc1527b2e8d3a940065b}, author = {Rodrigo de Luis-Garc{\'\i}a and Marcos Martin-Fernandez and J I Arribas and Carlos Alberola-Lopez} } @article {aja2003fuzzy, title = {A fuzzy-controlled Kalman filter applied to stereo-visual tracking schemes}, journal = {Signal Processing}, volume = {83}, number = {1}, year = {2003}, pages = {101{\textendash}120}, publisher = {Elsevier}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @proceedings {de2003model, title = {A model-based algorithm for the automatic segmentation of metacarpals in handwrist radiographs using active contours}, year = {2003}, pages = {80{\textendash}81}, author = {Rodrigo de Luis-Garc{\'\i}a and Marcos Martin-Fernandez and Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {martin2003novel, title = {A novel Gauss-Markov random field approach for regularization of diffusion tensor maps}, booktitle = {Computer Aided Systems Theory-EUROCAST 2003}, year = {2003}, pages = {506{\textendash}517}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Marcos Martin-Fernandez and Raul San Jose-Estepar and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {alberola2003simple, title = {A simple test of equality of time series}, journal = {Signal processing}, volume = {83}, number = {6}, year = {2003}, pages = {1343{\textendash}1348}, publisher = {Elsevier}, author = {Carlos Alberola-Lopez and Marcos Martin-Fernandez} } @article {san2003theoretical, title = {A theoretical framework to three-dimensional ultrasound reconstruction from irregularly sampled data}, journal = {Ultrasound in medicine \& biology}, volume = {29}, number = {2}, year = {2003}, pages = {255{\textendash}269}, publisher = {Elsevier}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Caballero-Mart{\'\i}nez, P Pablo and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @inbook {martin2002bayesian, title = {A Bayesian Approach to in vivo Kidney Ultrasound Contour Detection Using Markov Random Fields}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textemdash}MICCAI 2002}, year = {2002}, pages = {397{\textendash}404}, publisher = {Springer}, organization = {Springer}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {aja2002fuzzy, title = {A fuzzy MHT algorithm applied to text-based information tracking}, journal = {Fuzzy Systems, IEEE Transactions on}, volume = {10}, number = {3}, year = {2002}, pages = {360{\textendash}374}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Cybenko, George V} } @proceedings {de2002neural, title = {A neural architecture for bone age assessment}, year = {2002}, pages = {161{\textendash}166}, author = {Rodrigo de Luis-Garc{\'\i}a and J I Arribas and Santiago Aja-Fern{\'a}ndez and Lopez, C Alberola} } @conference {aja2001fuzzy, title = {Fuzzy anisotropic diffusion for speckle filtering}, booktitle = {Acoustics, Speech, and Signal Processing, 2001. Proceedings.(ICASSP{\textquoteright}01). 2001 IEEE International Conference on}, volume = {2}, year = {2001}, pages = {1261{\textendash}1264}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @conference {martin2001maximum, title = {Maximum likelihood contour estimation using beta-statistics in ultrasound images}, booktitle = {Image and Signal Processing and Analysis, 2001. ISPA 2001. Proceedings of the 2nd International Symposium on}, year = {2001}, pages = {207{\textendash}212}, publisher = {IEEE}, organization = {IEEE}, author = {Marcos Martin-Fernandez and Raul San Jose-Estepar and Carlos Alberola-Lopez} } @conference {martin2001multiresolution, title = {Multiresolution compression schemes for medical image and volume data}, booktitle = {Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE}, volume = {3}, year = {2001}, pages = {2437{\textendash}2440}, publisher = {IEEE}, organization = {IEEE}, author = {Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez and Sanz de Acedo, Jorge and Juan Ruiz-Alzola} } @conference {san2001reshaping, title = {Reshaping polygonal meshes with smoothed normals extracted from ultrasound volume data: An optimization approach}, booktitle = {Medical Imaging 2001}, year = {2001}, pages = {462{\textendash}472}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Raul San Jose-Estepar and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @article {martín2001topology, title = {A topology-based filling algorithm}, journal = {Computers \& Graphics}, volume = {25}, number = {3}, year = {2001}, pages = {493{\textendash}509}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @conference {martin2000coding, title = {Coding technique with progressive reconstruction based on VQ and entropy coding applied to medical images}, booktitle = {International Symposium on Optical Science and Technology}, year = {2000}, pages = {171{\textendash}181}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Marcos Martin-Fernandez and Carlos Alberola-Lopez and Guerrero-Rodriguez, David and Juan Ruiz-Alzola} } @conference {martin2000energy, title = {Energy functions for the segmentation of ultrasound volume data using active rays}, booktitle = {Acoustics, Speech, and Signal Processing, 2000. ICASSP{\textquoteright}00. Proceedings. 2000 IEEE International Conference on}, volume = {6}, year = {2000}, pages = {2274{\textendash}2277}, publisher = {IEEE}, organization = {IEEE}, author = {Marcos Martin-Fernandez and Rodriguez, E and Tejada, D and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @conference {estepar2000kalman, title = {Kalman filter technique applied to surface reconstruction and visualization from noisy volume data}, booktitle = {Medical Imaging 2000}, year = {2000}, pages = {396{\textendash}407}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Raul San Jose-Estepar and Rivera, Alberto and Pinacho, Marco and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @article {ruiz2000model, title = {Model-based stereo-visual tracking: Covariance analysis and tracking schemes}, journal = {Signal Processing}, volume = {80}, number = {1}, year = {2000}, pages = {23{\textendash}43}, publisher = {Elsevier}, author = {Juan Ruiz-Alzola and Carlos Alberola-Lopez and Corredera, Jose-Ram{\'o}n Casar} } @inbook {alberola2000disnei, title = {disnei: A collaborative environment for medical images analysis and visualization}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2000}, year = {2000}, publisher = {Springer}, organization = {Springer}, author = {Carlos Alberola-Lopez and Rub{\'e}n C{\'a}rdenes-Almeida and Marcos Martin-Fernandez and Miguel Angel Martin-Fernandez and Rodr{\'\i}guez-Florido, Miguel and Juan Ruiz-Alzola} } @article {409, title = {Cost functions to estimate a posteriori probabilities in multiclass problems}, journal = {IEEE Transactions on Neural Networks}, volume = {10}, year = {1999}, pages = {645-656}, abstract = {

The problem of designing cost functions to estimate a posteriori probabilities in multiclass problems is addressed in this paper. We establish necessary and sufficient conditions that these costs must satisfy in one-class one-output networks whose outputs are consistent with probability laws. We focus our attention on a particular subset of the corresponding cost functions; those which verify two usually interesting properties: symmetry and separability (well-known cost functions, such as the quadratic cost or the cross entropy are particular cases in this subset). Finally, we present a universal stochastic gradient learning rule for single-layer networks, in the sense of minimizing a general version of these cost functions for a wide family of nonlinear activation functions.

}, keywords = {Cost functions, Estimation, Functions, Learning algorithms, Multiclass problems, Neural networks, Pattern recognition, Probability, Problem solving, Random processes, Stochastic gradient learning rule}, issn = {10459227}, doi = {10.1109/72.761724}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0032643080\&partnerID=40\&md5=d528195bd6ec84531e59ddd2ececcd46}, author = {Jes{\'u}s Cid-Sueiro and J I Arribas and S Urban-Munoz and A R Figueiras-Vidal} } @conference {412, title = {Estimates of constrained multi-class a posteriori probabilities in time series problems with neural networks}, booktitle = {Proceedings of the International Joint Conference on Neural Networks}, year = {1999}, publisher = {IEEE, United States}, organization = {IEEE, United States}, address = {Washington, DC, USA}, abstract = {

In time series problems, where time ordering is a crucial issue, the use of Partial Likelihood Estimation (PLE) represents a specially suitable method for the estimation of parameters in the model. We propose a new general supervised neural network algorithm, Joint Network and Data Density Estimation (JNDDE), that employs PLE to approximate conditional probability density functions for multi-class classification problems. The logistic regression analysis is generalized to multiple class problems with softmax regression neural network used to model the a-posteriori probabilities such that they are approximated by the network outputs. Constraints to the network architecture, as well as to the model of data, are imposed, resulting in both a flexible network architecture and distribution modeling. We consider application of JNDDE to channel equalization and present simulation results.

}, keywords = {Approximation theory, Computer simulation, Constraint theory, Data structures, Joint network-data density estimation (JNDDE), Mathematical models, Multi-class a posteriori probabilities, Neural networks, Partial likelihood estimation (PLE), Probability density function, Regression analysis}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033325263\&partnerID=40\&md5=8c6134020b0b2a9c5ab05b131c070b88}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and T Adali and H Ni and B Wang and A R Figueiras-Vidal} } @conference {tardon1999markov, title = {Markov random fields and the disparity gradient constraint applied to stereo correspondence}, booktitle = {Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on}, volume = {3}, year = {1999}, pages = {901{\textendash}905}, publisher = {IEEE}, organization = {IEEE}, author = {Lorenzo J Tard{\'o}n-Garc{\'\i}a and Javier Portillo-Garcia and Carlos Alberola-Lopez} } @conference {411, title = {Neural architectures for parametric estimation of a posteriori probabilities by constrained conditional density functions}, booktitle = {Neural Networks for Signal Processing - Proceedings of the IEEE Workshop}, year = {1999}, publisher = {IEEE, Piscataway, NJ, United States}, organization = {IEEE, Piscataway, NJ, United States}, address = {Madison, WI, USA}, abstract = {

A new approach to the estimation of {\textquoteright}a posteriori{\textquoteright} class probabilities using neural networks, the Joint Network and Data Density Estimation (JNDDE), is presented in this paper. It is based on the estimation of the conditional data density functions, with some restrictions imposed by the classifier structure; the Bayes{\textquoteright} rule is used to obtain the {\textquoteright}a posteriori{\textquoteright} probabilities from these densities. The proposed method is applied to three different network structures: the logistic perceptron (for the binary case), the softmax perceptron (for multi-class problems) and a generalized softmax perceptron (that can be used to map arbitrarily complex probability functions). Gaussian mixture models are used for the conditional densities. The method has the advantage of establishing a distinction between the network parameters and the model parameters. Complexity on any of them can be fixed as desired. Maximum Likelihood gradient-based rules for the estimation of the parameters can be obtained. It is shown that JNDDE exhibits a more robust convergence characteristics than other methods of a posteriori probability estimation, such as those based on the minimization of a Strict Sense Bayesian (SSB) cost function.

}, keywords = {Asymptotic stability, Constraint theory, Data structures, Gaussian mixture models, Joint network and data density estimation, Mathematical models, Maximum likelihood estimation, Neural networks, Probability}, doi = {https://doi.org/10.1109/NNSP.1999.788145}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033321049\&partnerID=40\&md5=7967fa377810cc0c3e6a4d9020024b80}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and T Adali and A R Figueiras-Vidal} } @conference {410, title = {Neural networks to estimate ML multi-class constrained conditional probability density functions}, booktitle = {Proceedings of the International Joint Conference on Neural Networks}, year = {1999}, publisher = {IEEE, United States}, organization = {IEEE, United States}, address = {Washington, DC, USA}, abstract = {

In this paper, a new algorithm, the Joint Network and Data Density Estimation (JNDDE), is proposed to estimate the {\textquoteleft}a posteriori{\textquoteright} probabilities of the targets with neural networks in multiple classes problems. It is based on the estimation of conditional density functions for each class with some restrictions or constraints imposed by the classifier structure and the use Bayes rule to force the a posteriori probabilities at the output of the network, known here as a implicit set. The method is applied to train perceptrons by means of Gaussian mixture inputs, as a particular example for the Generalized Softmax Perceptron (GSP) network. The method has the advantage of providing a clear distinction between the network architecture and the model of the data constraints, giving network parameters or weights on one side and data over parameters on the other. MLE stochastic gradient based rules are obtained for JNDDE. This algorithm can be applied to hybrid labeled and unlabeled learning in a natural fashion.

}, keywords = {Generalized softmax perceptron (GSP) network, Joint network and data density estimation (JNDDE), Mathematical models, Maximum likelihood estimation, Neural networks, Probability density function, Random processes}, doi = {https://doi.org/10.1109/IJCNN.1999.831174}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033326060\&partnerID=40\&md5=bb38c144dac0872f3a467dc12170e6b6}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and T Adali and A R Figueiras-Vidal} } @article {alberola1999object, title = {Object CFAR detection in gamma-distributed textured-background images}, journal = {IEE Proceedings-Vision, Image and Signal Processing}, volume = {146}, number = {3}, year = {1999}, pages = {130{\textendash}136}, publisher = {IEE}, author = {Carlos Alberola-Lopez and JR Casar-Corredera and de Miguel-Vela, G} } @conference {martin1999novel, title = {A novel error criterion for multiresolution volume data compression}, booktitle = {[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint}, volume = {2}, year = {1999}, pages = {1159{\textendash}vol}, publisher = {IEEE}, organization = {IEEE}, author = {Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @article {portillo1998efficient, title = {Efficient multispectral texture segmentation using multivariate statistics}, journal = {IEE Proceedings-Vision, Image and Signal Processing}, volume = {145}, number = {5}, year = {1998}, pages = {357{\textendash}364}, publisher = {IEE}, author = {Javier Portillo-Garcia and Juan I Trueba-Santander and de Miguel-Vela, G and Carlos Alberola-Lopez} } @proceedings {hornero1997dsp, title = {A DSP Implementation of Wavelet Transform to Detect Epileptiform Activity in the EEG}, year = {1997}, pages = {692{\textendash}696}, author = {Hornero, R and Marcos Martin-Fernandez and Alonso, A and Izquierdo, A and Lopez, M} } @conference {450, title = {A Comparison of CFAR Strategies for Blob Detection in Textured Images}, booktitle = {European Signal Processing Conference (EUSIPCO), 1996}, year = {1996}, publisher = {Elsevier}, organization = {Elsevier}, author = {Carlos Alberola-Lopez and Casar-Corredera, Jos{\'e} Ramon and Juan Ruiz-Alzola} } @conference {tardon1996hypothesis, title = {Hypothesis testing for coarse region estimation and stable point determination applied to Markovian texture segmentation}, booktitle = {Image Processing, 1996. Proceedings., International Conference on}, volume = {3}, year = {1996}, pages = {169{\textendash}172}, publisher = {IEEE}, organization = {IEEE}, author = {Lorenzo J Tard{\'o}n-Garc{\'\i}a and Javier Portillo-Garcia and Carlos Alberola-Lopez and Juan I Trueba-Santander} } @proceedings {alberola1996region, title = {A Region Oriented CFAR Approach to the Detection of Extensive Targets in Textured Images}, year = {1996}, pages = {195}, publisher = {Elsevier Science Ltd}, author = {Carlos Alberola-Lopez and Casar-Corredera, Jos{\'e} Ramon and Juan Ruiz-Alzola} }