
Proceedings Paper
Build 4-dimensional myocardial model for dynamic CT imagesFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
4D (3D + time) model is valuable in comprehensive assessment of cardiac functions. Usually, the generation of the 4D
myocardial models involves myocardium segmentation, mesh generation and non-rigid registration (to build mesh node
correspondence). In this paper, we present a method to simultaneously perform the above tasks. This method begins from
a triangular surface model of the myocardium at the first phase of a cardiac cycle. Then, the myocardial surface is
simulated as a linear elastic membrane, and evolves toward the next phase governed by an energy function while
maintaining the mesh quality. Our preliminary experiments performed on dynamic CT images of the dog demonstrated
the effectiveness of this method on both segmentation and mesh generation. The minimum average surface distance
between the segmentation results of the proposed method and the ground truth can reach 0.72 ± 0.55 mm, and the mesh
quality measured by the aspect ratio of the triangle was less than 11.57 ± 1.18.
Paper Details
Date Published: 13 March 2013
PDF: 8 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86691Q (13 March 2013); doi: 10.1117/12.2007070
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
PDF: 8 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86691Q (13 March 2013); doi: 10.1117/12.2007070
Show Author Affiliations
Yixun Liu, National Institutes of Health (United States)
Songtao Liu, National Institutes of Health (United States)
Albert C. Lardo, National Institutes of Health (United States)
Karl Schuleri, National Institutes of Health (United States)
Songtao Liu, National Institutes of Health (United States)
Albert C. Lardo, National Institutes of Health (United States)
Karl Schuleri, National Institutes of Health (United States)
Marcelo Souto Nacif, National Institutes of Health (United States)
David A. Bluemke, National Institutes of Health (United States)
Ronald M. Summers , National Institutes of Health (United States)
Jianhua Yao, National Institutes of Health (United States)
David A. Bluemke, National Institutes of Health (United States)
Ronald M. Summers , National Institutes of Health (United States)
Jianhua Yao, National Institutes of Health (United States)
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
© SPIE. Terms of Use
