DocumentCode :
2078885
Title :
A multi-scale method for extraction of cerebral blood vessles
Author :
Zhao, Shifeng ; Wu, Zhongke ; Zhou, Mingquan
Author_Institution :
Coll. of Inf. Sci. & Technol., Beijing Normal Univ., Beijing, China
Volume :
2
fYear :
2010
fDate :
10-12 Dec. 2010
Firstpage :
1280
Lastpage :
1283
Abstract :
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.
Keywords :
biomedical MRI; blood vessels; feature extraction; image segmentation; medical image processing; splines (mathematics); trees (mathematics); Frangi vesselness measure; MRA datasets; ball B-spline method; cerebral blood vessel extraction; cerebral blood vessel segmentation; magnetic resonance angiography; medical image analysis; multiscale method; Biomedical imaging; Computers; Image edge detection; Image segmentation; cerebral blood vessel; multi-scale; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Progress in Informatics and Computing (PIC), 2010 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-6788-4
Type :
conf
DOI :
10.1109/PIC.2010.5687927
Filename :
5687927
Link To Document :
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