A multi-scale method for extraction of cerebral blood vessles
Shifeng Zhao, Zhongke Wu, Mingquan Zhou · 2010
Segmentation is one of the most challenging problems in the field of medical image analysis, and blood vessels are especially difficult to extract. In this paper, we propose a novel method for segmentation of cerebral blood vessels from magnetic resonance angiography (MRA) images based on Frangi's vesselness measure and ball B-Spline. First, we apply Frangi's vesselness measure to find putative centerlines of tubular structures along with their estimated radii. Then the ball B-Spline method is adopted to construct the 3D vascular trees. Results on head MRA datasets demonstrate the availability of the method.