A Topology Preserving Deformable Model Using Level Sets

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 nonintersecting curves (or surfaces). Several experiments on simulated and real data are provided to demonstrate the performance of the proposed algorithm.

• Type: Conference
• Year: 2001
• Where: CVPR
• Authors: Xiao Han, Chenyang Xu, Jerry L. Prince
• Keywords: Computer Vision, CVPR 2001, Digital Topology, Geometric Deformable Models, Powerful Segmentation Techniques, Surface Models, Topology Changes