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A Topology Preserving Deformable Model Using Level Sets
Kauai, Hawaii December 08-December 14
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2001.9910422001 IEEE Computer Society Conference ...
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Xiao Han, Johns Hopkins University
Chenyang Xu, Siemens Corporate Research
Jerry L. Prince, Johns Hopkins University
Active contour and surface models, also known as deformable models, constitute a class of powerful segmentation techniques. Geometric deformable models implemented via level-set methods have advantages over parametric ones due to their intrinsic behavior, parameterization independence, and ease of implementation. However, a long claimed advantage of geometric deformable models - the ability to automatically handle topology changes - turns out to be a liability in applications where the objects to be segmented have a known topology that must be preserved. In this paper, we present a geometric deformable model that preserves topology using the simple point concept from digital topology. This algorithm maintains the other advantages of standard geometric deformable models including sub-pixel accuracy and production of non-intersecting curves (or surfaces). Several experiments on simulated and real data are provided to demonstrate the performance of the proposed algorithm.
Citation:
Xiao Han, Chenyang Xu, Jerry L. Prince, "A Topology Preserving Deformable Model Using Level Sets," cvpr, vol. 2, pp.765, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 2, 2001
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