Vessel Extraction Using Anisotropic Minimal Paths and Path Score
Chen, Da; Cohen, Laurent D.; Mirebeau, Jean-Marie (2014), Vessel Extraction Using Anisotropic Minimal Paths and Path Score, 2014 IEEE International Conference on Image Processing (ICIP 2014), IEEE : Piscataway, NJ. 10.1109/ICIP.2014.7025314
TypeCommunication / Conférence
Book title2014 IEEE International Conference on Image Processing (ICIP 2014); IEEE International Conference on Image Processing (ICIP 2014)
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Abstract (EN)Geodesic methods have been widely applied to image analysis . They are particularly efficient to extract a tubular structure, such as a blood vessel, given its two endpoints in a 2D or 3D medical image . We address here a more difficult problem: the extraction of a full vessel tree structure given a single initial root, by growing a collection of keypoints, connected by geodesic minimal paths as in . Keypoints are iteratively added, using selection criteria which compare geodesic distances with the standard euclidean curve length and a path score. A weakness of existing approaches is that the geodesic length and the euclidean path length are locally proportional, due to the use of an isotropic geodesic potential P(x). In contrast, we use an anisotropic geodesic potential P(x, v), and develop new criteria for selecting keypoints and stopping the tree growth. Experimental results demonstrate that our method can extract vessel structures at a finer scale, with increased accuracy.
Subjects / KeywordsGeodesic methods; Vessel extraction; Anisotropic Fast Marching; Minimal Paths; Keypoints
Showing items related by title and author.
Vessel Tree Extraction using Radius-Lifted Keypoints Searching Scheme and Anisotropic Fast Marching Method Chen, Da; Mirebeau, Jean-Marie; Cohen, Laurent D. (2016) Article accepté pour publication ou publié
Vessel Extraction Using Crossing-Adaptive Minimal Path Model with Anisotropic Enhancement and Curvature Constraint Liu, Li; Chen, Da; Cohen, Laurent D.; Huazhong, Shu; Pâques, Michel (2019) Communication / Conférence