A Near-Incompressible Poly-Affine Motion Model for Cardiac Function Analysis

Abstract : Understanding the motion of the heart through the cardiac cycle can give useful insight for a range of different pathologies. In par- ticular, quantifying regional cardiac motion can help clinicians to better determine cardiac function by identifying regions of thickened, ischemic or infarcted tissue. In this work we propose a method for cardiac motion analysis to track the deformation of the left ventricle at a regional level. This method estimates the affine motion of distinct regions of the my- ocardium using a near incompressible non-rigid registration algorithm based on the Demon's optical flow approach. The global motion over the ventricle is computed by a smooth fusion of the deformation in each seg- ment using an anatomically aware poly-affine model for the heart. We apply the proposed method to a data-set of 10 volunteers. The results in- dicate that we are able to extract reasonably realistic deformation fields parametrised by a significantly reduced number of parameters compared to voxel-wise methods, which better enables for statistical analyses of the motion.
Type de document :
Communication dans un congrès
Proc. MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function + a Cardiac Electrophysiological Simulation Challenge (STACOM+CESC'12), 2012, Nice, France. Springer, 7746, pp.288-297, 2013, Lecture Notes in Computer Science - LNCS. 〈10.1007/978-3-642-36961-2_33〉
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https://hal.inria.fr/hal-00813852
Contributeur : Project-Team Asclepios <>
Soumis le : mardi 16 avril 2013 - 11:18:56
Dernière modification le : mercredi 30 mai 2018 - 13:56:03

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Kristin Mcleod, Christof Seiler, Maxime Sermesant, Xavier Pennec. A Near-Incompressible Poly-Affine Motion Model for Cardiac Function Analysis. Proc. MICCAI Workshop on Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function + a Cardiac Electrophysiological Simulation Challenge (STACOM+CESC'12), 2012, Nice, France. Springer, 7746, pp.288-297, 2013, Lecture Notes in Computer Science - LNCS. 〈10.1007/978-3-642-36961-2_33〉. 〈hal-00813852〉

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