@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} } @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 {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} }