Modeling, analysis, and visualization of left ventricle shape andmotion by hierarchical decomposition
Chang Wen Chen
Huang, T.S.
Arrott, M.
Dept. of Electr. Eng., Rochester Univ., NY;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Apr 1994
Volume: 16,
Issue: 4
On page(s): 342-356
ISSN: 0162-8828
References Cited: 38
CODEN: ITPIDJ
INSPEC Accession Number: 4679822
Digital Object Identifier: 10.1109/34.277589
Current Version Published: 2002-08-06
Abstract
This paper presents an approach to the modeling, analysis, and
visualization of left ventricle motion and deformation. The authors'
modeling of left ventricle shape and motion as a hierarchical
representation enables them to develop a promising noninvasive technique
for monitoring heart dynamics where both image analysis and image
synthesis are involved. The proposed hierarchical motion model of left
ventricle is constructed by combining several existing simple models and
is able to capture major motion and deformation components of the left
ventricle. The hierarchical decomposition characterizes the left
ventricle motion and deformation in a coarse-to-fine fashion and leads
to computationally efficient estimation algorithms. The authors estimate
the global rigid motion of the left ventricle by establishing a
time-varying object-centered coordinate system. The global deformations
of the left ventricle are obtained by fitting the given data to
superquadric modeling primitives. The local deformations are estimated
by a tensor-description approach that is based on the locally deformable
surface obtained by constructing spherical harmonic local surface from
the residues of global shape estimation. The authors also describe in
this paper methods of image synthesis and dynamic animation for
visualizing the estimated results of the time-varying left ventricle
shape, motion, and deformations. These animation results are consistent
with the apparent motion pattern of the left ventricle and therefore
show the success of the authors' hierarchical decomposition based
approach
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