Blood Vessel Extraction Based on Mumford Shah Model and Skeletonization

Author

Lam, Benson S Y ; Yan, Hong

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

4227

Lastpage

4232

Abstract

Locating blood vessels in a retinal image has found wide applications in medical image for diagnosis of diseases. However, due to the presence of noise and uneven distributed image intensity, this is still a challenging task. In this paper, we introduce a new method based on the features that the blood vessel must be a thin concave connected region. Based on Mumford-Shah (MS) model and skeletonization method, the proposed method is able to extract many small branches of vessels. Experimental results show that the proposed method outperforms existing methods and able to yield good results in real world data sets

Keywords

blood vessels; diseases; eye; image thinning; medical image processing; Mumford Shah model; blood vessel extraction; disease diagnosis; distributed image intensity; medical image; retinal image; skeletonization method; Biomedical engineering; Biomedical imaging; Blood vessels; Data mining; Diseases; Image edge detection; Laplace equations; Machine learning; Matched filters; Medical diagnostic imaging; Optical noise; Retina; Skeleton; Blood vessels segmentation; Mumford-Shah model; Skeletonization; retinal imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258948

Filename

4028814