Publications

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A
Leal-Campanario, R., L. Alarcon-Martinez, H. Rieiro, S. Martinez-Conde, T. Alarcon-Martinez, X. Zhao, J. LaMee, P.J. Popp, M.E. Calhoun, J. I. Arribas, et al., "Abnormal Capillary Vasodynamics Contribute to Ictal Neurodegeneration in Epilepsy", Scientific Reports, vol. 7, 2017.
Veraart, J., S. Winzeck, Á. Planchuelo-Gómez, B. Fricke, E. N. Kornaropoulos, H. Merisaari, T. Pieciak, Y. Zou, and M. Descoteaux, "Assessing the variability of brain diffusion MRI preprocessing pipelines using a Region-of-Interest analysis", 2023 ISMRM & ISMRT Annual Meeting & Exhibition, vol. 5015, 2023.
C
Rabanillo-Viloria, I., A. Zhu, S. Aja-Fernández, C. Alberola-López, and D. Hernando, "Computation of exact g-factor maps in 3D GRAPPA reconstructions", Magnetic resonance in medicine, vol. 81, pp. 1353–1367, 2019.
D
Zhao, T., C. Luo, J. Zhou, D. Guo, N. Chen, and P. Casaseca-de-la-Higuera, "DoA Prediction Based Beamforming with Low Training Overhead for Highly-Mobile UAV Communication with Cellular Networks", Applied Sciences, vol. 10, no. 13: Multidisciplinary Digital Publishing Institute, pp. 4420, 2020.
Zhao, T., C. Luo, J. Zhou, D. Guo, N. Chen, and P. Casaseca-de-la-Higuera, "DoA Prediction Based Beamforming with Low Training Overhead for Highly-Mobile UAV Communication with Cellular Networks", Applied Sciences, vol. 10, no. 13: Multidisciplinary Digital Publishing Institute, pp. 4420, 2020.
M
Zhang, Y., Ó. Peña-Nogales, J. H. Holmes, and D. Hernando, "Monte-Carlo Analysis of Quantitative Diffusion Measurements Using Motion-Compensated Diffusion Weighting Waveforms", International Society of Magnetic Resonance in Medicine 25th Annual Meeting and Exhibition, Honolulu, HI, USA, pp. 1733, 2017.
Zhang, Y., Ó. Peña-Nogales, J. H. Holmes, and D. Hernando, "Motion-Robust and Blood-Suppressed M1-Optimized Diffusion MR Imaging of the Liver", ISMRM 27th annual meeting, vol. 116, 2019.
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Peña-Nogales, Ó., Y. Zhang, R. de Luis-García, S. Aja-Fernández, J. H. Holmes, and D. Hernando, "Optimal Diffusion-weighting Gradient Waveform Design (ODGD): Formulation and Experimental Validation", International Society of Magnetic Resonance in Medicine 26th Annual Meeting and Exhibition, Paris, France, pp. 685, 2018.
Peña-Nogales, Ó., R. de Luis-García, S. Aja-Fernández, Y. Zhang, J. H. Holmes, and D. Hernando, "Optimal design of motion-compensated diffusion gradient waveforms ", International Society of Magnetic Resonance in Medicine 25th Annual Meeting and Exhibition, Honolulu, HI, USA, pp. 3340, 2017.
Peña-Nogales, Ó., Y. Zhang, X. Wang, R. de Luis-García, S. Aja-Fernández, J. H. Holmes, and D. Hernando, "Optimized Diffusion-Weighting Gradient Waveform Design (ODGD) formulation for motion compensation and concomitant gradient nulling", Magnetic resonance in medicine, 2018.
Peña-Nogales, Ó., Y. Zhang, X. Wang, R. de Luis-García, S. Aja-Fernández, J. H. Holmes, and D. Hernando, "Optimized Diffusion-Weighting Gradient Waveform Design (ODGD) formulation for motion compensation and concomitant gradient nulling", Magnetic resonance in medicine, vol. 81, pp. 989–1003, 2019.
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Peña-Nogales, Ó., Y. Zhang, R. de Luis-García, S. Aja-Fernández, J. H. Holmes, and D. Hernando, "Reduced Eddy Current induced image distortions and Peripheral Nerve Stimulation based on the Optimal Diffusion-weighting Gradient Waveform Design (ODGD) formulation", ISMRM 27th annual meeting, vol. 3488, 2019.
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Fernández-Linsenbarth, I., Á. Planchuelo-Gómez, R. M. Beño-Ruiz-de-la-Sierra, A. Díez, A. Arjona, A. Pérez, A. Rodríguez-Lorenzana, P. del Valle, R. de Luis-García, G. Mascialino, et al., "Search for schizophrenia and bipolar biotypes using functional network properties", Brain and Behavior, vol. 11, pp. e2415, 2021.
Zhang, H., P. Casaseca-de-la-Higuera, C. Luo, Q. Wang, M. Kitchin, A. Parmley, and J. Monge-Alvarez, "Systematic infrared image quality improvement using deep learning based techniques", Remote Sensing Technologies and Applications in Urban Environments: International Society for Optics and Photonics, 2016.
V
Aja-Fernandez, S., C. Martin-Martin, T. Pieciak, Á. Planchuelo-Gómez, A. Faiyaz, N. Uddin, A. Tiwari, S. J. Shigwan, T. Zheng, Z. Cao, et al., "Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies", 2023 ISMRM & ISMRT Annual Meeting & Exhibition, vol. 2786, 2023.
Aja-Fernández, S., C. Martín-Martín, Á. Planchuelo-Gómez, A. Faiyaz, M. Nasir Uddin, G. Schifitto, A. Tiwari, S. J. Shigwan, R. Kumar Singh, T. Zheng, et al., "Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies", NeuroImage: Clinical, vol. 39, pp. 103483, 2023.
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De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", bioRxiv, 2021.
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", bioRxiv, 2021.
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", bioRxiv, 2021.
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", NeuroImage, pp. 118367, 2021.
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", NeuroImage, pp. 118367, 2021.
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", NeuroImage, pp. 118367, 2021.
N
Zhang, H., C. Luo, Q. Wang, M. Kitchin, A. Parmley, J. Monge-Alvarez, and P. Casaseca-de-la-Higuera, "A novel infrared video surveillance system using deep learning based techniques", Multimedia Tools and Applications, vol. 77, issue 26676, 2018.