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Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps.

, , , , , and . Eng. Comput., 38 (5): 3957-3973 (2022)

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Learning Atrial Fiber Orientations and Conductivity Tensors from Intracardiac Maps Using Physics-Informed Neural Networks., , , , , , and . FIMH, volume 12738 of Lecture Notes in Computer Science, page 650-658. Springer, (2021)Smoothness and continuity of cost functionals for ECG mismatch computation., , and . CoRR, (2022)Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps., , , , , and . Eng. Comput., 38 (5): 3957-3973 (2022)An inverse Eikonal method for identifying ventricular activation sequences from epicardial activation maps., , , , , , and . J. Comput. Phys., (2020)Optimizing Wavelet Bases for Sparser Representations., and . EMMCVPR, volume 10746 of Lecture Notes in Computer Science, page 249-262. Springer, (2017)A Fast Iterative Method Python package.. J. Open Source Softw., 6 (66): 3641 (2021)Digital Twinning of Cardiac Electrophysiology Models From the Surface ECG: A Geodesic Backpropagation Approach., , , , and . IEEE Trans. Biomed. Eng., 71 (4): 1281-1288 (April 2024)A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs., , , , , , , , , and 6 other author(s). Medical Image Anal., (2021)PIEMAP: Personalized Inverse Eikonal Model from Cardiac Electro-Anatomical Maps., , , , , and . M&Ms and EMIDEC/STACOM@MICCAI, volume 12592 of Lecture Notes in Computer Science, page 76-86. Springer, (2020)GEASI: Geodesic-based Earliest Activation Sites Identification in cardiac models., , , , , and . CoRR, (2021)