Tubular Anisotropy Segmentation
Benmansour, Fethallah; Cohen, Laurent D. (2009), Tubular Anisotropy Segmentation, in Tai, Xue-Cheng, Knut Morken, Marius Lysaker, Knut-Andreas Lie, Scale Space and Variational Methods in Computer Vision Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings, Springer : Berlin Heidelberg, p. 14-25. 10.1007/978-3-642-02256-2_2
TypeCommunication / Conférence
Book titleScale Space and Variational Methods in Computer Vision Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings
Book authorTai, Xue-Cheng, Knut Morken, Marius Lysaker, Knut-Andreas Lie
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Abstract (EN)In this paper 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 giving higher speed on the center of the vessels and also when the minimal path tangent is coherent with the vessel’s direction. 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.
Subjects / KeywordsVessel segmentation; Multi-scale; Minimal path method; Anisotropy; Enhancement; Fast marching algorithm
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