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Combining atlas and active contour for automatic 3D medical image segmentation

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2 Author(s)
Yi Gao ; Georgia Institute of Technology, Schools of Electrical Computer Engineering and Department of Biomedical Engineering, Atlanta, 30332-0250, U.S.A. ; Allen Tannenbaum

Atlas based methods and active contours are two families of techniques widely used for the task of 3D medical image segmentation. In this work we present a coupled framework where the two methods are combined together, in order to exploit each's advantage while avoid their respective drawbacks. Indeed, the atlas based methods lacks the flexibility in locally tuning the segmentation boundary; whereas the active contour has the drawback that the final result heavily depends on the initialization as well as the contour evolution energy functional. Therefore, in the proposed work, the atlas based segmentation provides a probability map, which not only supplies the initial contour position, but also defines the contour evolution energy in an on-line fashion. Afterward, the active contour further converges to the desired object boundary. Finally, the method is tested on various 3D medical images to demonstrate its robustness as well as accuracy.

Published in:

2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

Date of Conference:

March 30 2011-April 2 2011