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Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling., , , , , , , , , and 4 other author(s). CoRR, (2019)Joint analysis of clinical risk factors and 4D cardiac motion for survival prediction using a hybrid deep learning network., , , , , , and . CoRR, (2019)CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy., , , , , , and . IEEE Trans. Medical Imaging, 43 (3): 1259-1269 (March 2024)Three-dimensional cardiovascular imaging-genetics: a mass univariate framework., , , , , , , , , and 3 other author(s). Bioinform., 34 (1): 97-103 (2018)Deep learning cardiac motion analysis for human survival prediction., , , , , , , , , and 1 other author(s). CoRR, (2018)Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach., , , , , , , , , and . CoRR, (2018)Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach., , , , , , , , , and . IEEE Trans. Med. Imaging, 38 (9): 2151-2164 (2019)Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images., , , , , , , , , and . IEEE Trans. Medical Imaging, 36 (1): 332-342 (2017)Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models., , , , , , , , , and 5 other author(s). IEEE Trans. Medical Imaging, 39 (6): 2088-2099 (2020)Deep-learning cardiac motion analysis for human survival prediction., , , , , , , , , and 1 other author(s). Nat. Mach. Intell., 1 (2): 95-104 (2019)