Vascular segmentation algorithm using locally adaptive region growing based on centerline estimation

Jaeyoun Yi; Jong Beom Ra

doi:10.1117/12.431012

3 July 2001 Vascular segmentation algorithm using locally adaptive region growing based on centerline estimation

Jaeyoun Yi, Jong Beom Ra

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431012
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

In this paper, we propose a new region-based approach on the basis of centerline estimation, to segment vascular networks in 3D CTA/MRA images. The proposed algorithm is applied repeatedly to newly updated local cubes. It consists of three tasks; local region growing, surfacic connected component labeling, and next local cube detection. The cube size is adaptively determined according to the estimated diameter. After region growing inside a local cube, we perform the connected component labeling procedure on all 6 faces of the current local cube (surfacic component labeling). Then the detected surfacic components are put into a queue to serve as seeds of following local cubes. Contrary to conventional centerline-tracking methods, the proposed algorithm can detect all bifurcations without any restriction because a region-based method is used at every local cube. And by confining region growing to a local cube, it can be more effective in producing prospective results. It should be noticed that the segmentation result is divided into several branches, so a user can easily edit the result branch-by-branch. The proposed method can automatically generate a flyway in a virtual angioscopic system since it provides a tree structure of the detected branches.

Citation Download Citation

Jaeyoun Yi and Jong Beom Ra "Vascular segmentation algorithm using locally adaptive region growing based on centerline estimation", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431012

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