Personalization of a Cardiac Electromechanical Model using Reduced Order Unscented Kalman Filtering from Regional Volumes

Abstract : Patient-specific cardiac modelling can help in understanding pathophysiology and therapy planning. However it requires to combine functional and anatomical data in order to build accurate models and to personalize the model geometry, kinematics, electrophysiology and mechanics. Personalizing the electromechanical coupling from medical images is a challenging task. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reasonable number of parameters (14 for each ventricle) compared to the available clinical data at the organ level. We propose a personalization strategy from cine MRI data in two steps. We first estimate global parameters with an automatic calibration algorithm based on the Unscented Transform which allows to initialize the parameters while matching the volume and pressure curves. In a second step we locally personalize the contractilities of all AHA (American Heart Association) zones of the left ventricle using the Reduced Order Unscented Kalman Filtering on Regional Volumes. This personalization strategy was validated synthetically and tested successfully on eight healthy and three pathological cases.
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Article dans une revue
Medical Image Analysis, Elsevier, 2013, 17 (7), pp.816-829. 〈10.1016/j.media.2013.04.012〉
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Contributeur : Stephanie Marchesseau <>
Soumis le : jeudi 2 mai 2013 - 13:58:43
Dernière modification le : jeudi 19 avril 2018 - 14:24:03
Document(s) archivé(s) le : lundi 19 août 2013 - 11:35:16

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Stéphanie Marchesseau, Hervé Delingette, Maxime Sermesant, Rocio Cabrera Lozoya, Catalina Tobon-Gomez, et al.. Personalization of a Cardiac Electromechanical Model using Reduced Order Unscented Kalman Filtering from Regional Volumes. Medical Image Analysis, Elsevier, 2013, 17 (7), pp.816-829. 〈10.1016/j.media.2013.04.012〉. 〈hal-00819806〉

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