Personalization of Cardiac Motion and Contractility from Images using Variational Data Assimilation

Abstract : Personalization is a key aspect of biophysical models in order to impact clinical practice. In this paper, we propose a personalization method of electromechanical models of the heart from cine-MR images based on the adjoint method. After estimation of electrophysiological parameters, the cardiac motion is estimated based on a proactive electromechanical model. Then cardiac contractilities on two or three regions are estimated by minimizing the discrepancy between measured and simulation motion. Evaluation of the method on three patients with infarcted or dilated myocardium is provided.
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IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2012, 59 (1), pp.20-24. 〈10.1109/TBME.2011.2160347〉
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https://hal.inria.fr/inria-00616183
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Dernière modification le : jeudi 11 janvier 2018 - 16:17:48
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Hervé Delingette, Florence Billet, Ken C.L. Wong, Maxime Sermesant, Kawal Rhode, et al.. Personalization of Cardiac Motion and Contractility from Images using Variational Data Assimilation. IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2012, 59 (1), pp.20-24. 〈10.1109/TBME.2011.2160347〉. 〈inria-00616183〉

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