Tubular Structure Segmentation Based on Minimal Path Method and Anisotropic Enhancement
Benmansour, Fethallah; Cohen, Laurent D. (2011), Tubular Structure Segmentation Based on Minimal Path Method and Anisotropic Enhancement, International Journal of Computer Vision, 92, 2, p. 192-210. http://dx.doi.org/10.1007/s11263-010-0331-0
TypeArticle accepté pour publication ou publié
Journal nameInternational Journal of Computer Vision
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Cohen, Laurent D.
Abstract (EN)We present a new interactive method for tubular structure extraction. The main application and motivation for this work is vessel tracking in 2D and 3D images. The basic tools are minimal paths solved using the fast marching algorithm. This allows interactive tools for the physician by clicking on a small number of points in order to obtain a minimal path between two points or a set of paths in the case of a tree structure. Our method is based on a variant of the minimal path method that models the vessel as a centerline and surface. This is done by adding one dimension for the local radius around the centerline. The crucial step of our method is the definition of the local metrics to minimize. We have chosen to exploit the tubular structure of the vessels one wants to extract to built an anisotropic metric. The designed metric is well oriented along the direction of the vessel, admits higher velocity on the centerline, and provides a good estimate of the vessel radius. Based on the optimally oriented flux this measure is required to be robust against the disturbance introduced by noise or adjacent structures with intensity similar to the target vessel. We obtain promising results on noisy synthetic and real 2D and 3D images and we present a clinical validation.
Subjects / KeywordsVessel segmentation; Minimal path method; Fast marching algorithm; Anisotropy; Enhancement; Multi-scale
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