Share Email Print

Proceedings Paper

Advanced level set segmentation of the right atrium in MR
Author(s): Siqi Chen; Timo Kohlberger; Klaus J. Kirchberg
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Atrial fibrillation is a common heart arrhythmia, and can be effectively treated with ablation. Ablation planning requires 3D models of the patient's left atrium (LA) and/or right atrium (RA), therefore an automatic segmentation procedure to retrieve these models is desirable. In this study, we investigate the use of advanced level set segmentation approaches to automatically segment RA in magnetic resonance angiographic (MRA) volume images. Low contrast to noise ratio makes the boundary between the RA and the nearby structures nearly indistinguishable. Therefore, pure data driven segmentation approaches such as watershed and ChanVese methods are bound to fail. Incorporating training shapes through PCA modeling to constrain the segmentation is one popular solution, and is also used in our segmentation framework. The shape parameters from PCA are optimized with a global histogram based energy model. However, since the shape parameters span a much smaller space, it can not capture fine details of the shape. Therefore, we employ a second refinement step after the shape based segmentation stage, which follows closely the recent work of localized appearance model based techniques. The local appearance model is established through a robust point tracking mechanism and is learned through landmarks embedded on the surface of training shapes. The key contribution of our work is the combination of a statistical shape prior and a localized appearance prior for level set segmentation of the right atrium from MRA. We test this two step segmentation framework on porcine RA to verify the algorithm.

Paper Details

Date Published: 1 March 2011
PDF: 6 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 796431 (1 March 2011); doi: 10.1117/12.877728
Show Author Affiliations
Siqi Chen, Rensselaer Polytechnic Institute (United States)
Timo Kohlberger, Siemens Corporate Research (United States)
Klaus J. Kirchberg, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes III, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?