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Proceedings Paper

Local force model for cardiac dynamics analysis based on CT volumetric image sequences
Author(s): Jose Gerardo Tamez-Pena; Chang Wen Chen; Kevin J. Parker
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Paper Abstract

In this paper we present a local force model and its integration in a hierarchical analysis of the estimation of the left ventricle motion over a cardiac cycle. The local force model is derived from the dynamics of independent point masses driven by local constant forces over a short time. A force field is assumed to be constant over short periods of time. This force drives independent point masses within a regional patch of the left ventricle surface from one time instant to another. The trajectory that minimizes the energy required to move the point mass from one surface to another is considered as the local displacement vector. This estimated trajectory takes into account surface constraints and previous estimations derived from the volumetric image sequences so that the point masses travel along smooth trajectories resembling the realistic left ventricle surface dynamics. This proposed model is able to recover the point correspondence of the nonrigid motions between consecutive frames when the surfaces and the initial conditions of left ventricle at consecutive time frames are given. The local force model is incorporated in a hierarchical analysis scheme providing us with the complete dynamics of the left ventricle as compared to the local kinematic analysis of previous approaches. Experimental results based on synthetic and real left ventricle CT volumetric images show that the proposed scheme is very promising for cardiac analysis.

Paper Details

Date Published: 26 February 1997
PDF: 12 pages
Proc. SPIE 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision, (26 February 1997);
Show Author Affiliations
Jose Gerardo Tamez-Pena, Univ. of Rochester (United States)
Chang Wen Chen, Univ. of Missouri/Columbia (United States)
Kevin J. Parker, Univ. of Rochester (United States)

Published in SPIE Proceedings Vol. 2962:
25th AIPR Workshop: Emerging Applications of Computer Vision
David H. Schaefer; Elmer F. Williams, Editor(s)

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