Computing the differential characteristics of isointensity surface
Computer Vision and Image Understanding
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Physiome model based state-space framework for cardiac kinematics recovery
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Imaging of 3d cardiac electrical activity: a model-based recovery framework
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Recovering cardiac electrical activity from medical image sequence: a model-based approach
STACOM'10/CESC'10 Proceedings of the First international conference on Statistical atlases and computational models of the heart, and international conference on Cardiac electrophysiological simulation challenge
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Because of their physiological meaningfulness, cardiac physiome models have been used as constraints to recover patient information from medical images. Although the results are promising, the parameters of the physiome models are not patient-specific, and thus affect the clinical relevance of the recovered information especially in pathological cases. In view of this problem, we incorporate patient information from body surface potential maps in the physiome model to provide a more patient-specific while physiological plausible guidance, which is further coupled with patient measurements derived from structural images to recover the cardiac geometry and deformation simultaneously. Experiments have been conducted on synthetic data to show the benefits of the framework, and on real human data to show its practical potential.