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Proceedings Paper

Dynamic deformable models for 3D MRI heart segmentation
Author(s): Leonid Zhukov; Zhaosheng Bao; Igor Gusikov; John Wood; David E. Breen
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Paper Abstract

Automated or semiautomated segmentation of medical images decreases interstudy variation, observer bias, and postprocessing time as well as providing clincally-relevant quantitative data. In this paper we present a new dynamic deformable modeling approach to 3D segmentation. It utilizes recently developed dynamic remeshing techniques and curvature estimation methods to produce high-quality meshes. The approach has been implemented in an interactive environment that allows a user to specify an initial model and identify key features in the data. These features act as hard constraints that the model must not pass through as it deforms. We have employed the method to perform semi-automatic segmentation of heart structures from cine MRI data.

Paper Details

Date Published: 9 May 2002
PDF: 8 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467105
Show Author Affiliations
Leonid Zhukov, California Institute of Technology (United States)
Zhaosheng Bao, California Institute of Technology (United States)
Igor Gusikov, Univ. of Michigan (United States)
John Wood, Children's Hospital Los Angelos (United States)
David E. Breen, California Institute of Technology (United States)

Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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