A near-incompressible poly-affine motion model for cardiac function analysis

Authors:
Kristin McLeod;Christof Seiler;Maxime Sermesant;Xavier Pennec
Affiliations:
INRIA Méditerranée, ASCLEPIOS Project, Sophia Antipolis, France;INRIA Méditerranée, ASCLEPIOS Project, Sophia Antipolis, France,Institute for Surgical Technology and Biomechanics, University of Bern, Switzerland;INRIA Méditerranée, ASCLEPIOS Project, Sophia Antipolis, France;INRIA Méditerranée, ASCLEPIOS Project, Sophia Antipolis, France
Venue:
STACOM'12 Proceedings of the third international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Year:
2012

Citing 5
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An incompressible log-domain demons algorithm for tracking heart tissue

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Regional analysis of left ventricle function using a cardiac-specific polyaffine motion model

FIMH'13 Proceedings of the 7th international conference on Functional Imaging and Modeling of the Heart

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Abstract

Understanding the motion of the heart through the cardiac cycle can give useful insight for a range of different pathologies. In particular, 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 myocardium 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 segment using an anatomically aware poly-affine model for the heart. We apply the proposed method to a data-set of 10 volunteers. The results indicate 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.