A Locally Adaptive Region Growing Algorithm for Vascular Segmentation

摘要

To segment vascular structures in 3-D CTA/MRA images, this article presents a new region growing algorithm based on local cube tracking. In the proposed algorithm, a small local cube is segmented to detect a vessel segment, and the following local cube(s) is determined based on the segmentation result. This procedure is repeated until the segmentation is completed. By confining the segmentation inside each local cube, a robust result can be obtained even in a tubular structure of steadily changing intensity. For segmentation, a locally adaptive and competitive region growing scheme is adopted to obtain well-defined vessel boundaries. It should be emphasized that the proposed algorithm can detect all branches with practically acceptable computational complexity. In addition, its segmentation result is represented as a tree structure having many branches so that a user may easily correct the result branch-by-branch, if necessary. Experimental results from real images prove that the proposed algorithm produces prospective vessel segmentation results for 3-D CTA/MRA images and segments vessels of various sizes well, including stenoses and aneurysms.