Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review

The class of geometric deformable models, also known as level sets, has brought tremendous impact to medical imagery due to its capability of topology preservation and fast shape recovery. In an effort to facilitate a clear and full understanding of these powerful state-of-the-art applied mathematical tools, this paper is an attempt to explore these geometric methods, their implementations and integration of regularizers to improve the robustness of these topologically independent propagating curves/surfaces. This paper first presents the origination of level sets, followed by the taxonomy of level sets. We then derive the fundamental equation of curve/surface evolution and zero-level curves/surfaces. The paper then focuses on the first core class of level sets, known as "level sets without regularizers." This class presents five prototypes: gradient, edge, area-minimization, curvature-dependent and application driven. The next section is devoted to second core class of level...

• Type: Journal
• Year: 2002
• Where: TITB
• Authors: Jasjit S. Suri, Kecheng Liu, Sameer Singh, Swamy Laxminarayan, Xiaolan Zeng, Laura Reden
• Keywords: Core Class, Geometric Deformable Models, Level Sets, TITB 2002