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Cardiac motion estimation using a proactive deformable model: evaluation and sensitivity analysis

Ken C.L. Wong 1 Florence Billet 2, 1 Tommaso Mansi 1, * Radomir Chabiniok 3 Maxime Sermesant 1, * Hervé Delingette 1, * Nicholas Ayache 1, *
* Corresponding author
1 ASCLEPIOS - Analysis and Simulation of Biomedical Images
CRISAM - Inria Sophia Antipolis - Méditerranée
2 BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : To regularize cardiac motion recovery from medical images, electromechanical models are increasingly popular for providing a priori physiological motion information. Although these models are macroscopic, there are still many parameters to be specified for accurate and robust recovery. In this paper, we provide a sensitivity analysis of a pro-active electromechanical model-based cardiac motion tracking framework by studying the impacts of its model parameters. Our sensitivity analysis differs from other works by evaluating the motion recovery through a synthetic image sequence with known displacement field as well as cine and tagged MRI sequences. This analysis helps to identify which parameters should be estimated from patient-specific data and which ones can have their values set from the literature.
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Submitted on : Friday, August 19, 2011 - 7:33:27 PM
Last modification on : Friday, January 21, 2022 - 3:17:49 AM

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Ken C.L. Wong, Florence Billet, Tommaso Mansi, Radomir Chabiniok, Maxime Sermesant, et al.. Cardiac motion estimation using a proactive deformable model: evaluation and sensitivity analysis. STACOM - Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function; and CESC'10 -Cardiac Electrophysiological Simulation Challenge, held in Conjunction with MICCAI 2010, Sep 2010, Beijing, China. pp.154-163, ⟨10.1007/978-3-642-15835-3_16⟩. ⟨inria-00616152⟩



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