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Proceedings Paper

A novel retinal vessel extraction algorithm based on matched filtering and gradient vector flow
Author(s): Lei Yu; Mingliang Xia; Li Xuan
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Paper Abstract

The microvasculature network of retina plays an important role in the study and diagnosis of retinal diseases (age-related macular degeneration and diabetic retinopathy for example). Although it is possible to noninvasively acquire high-resolution retinal images with modern retinal imaging technologies, non-uniform illumination, the low contrast of thin vessels and the background noises all make it difficult for diagnosis. In this paper, we introduce a novel retinal vessel extraction algorithm based on gradient vector flow and matched filtering to segment retinal vessels with different likelihood. Firstly, we use isotropic Gaussian kernel and adaptive histogram equalization to smooth and enhance the retinal images respectively. Secondly, a multi-scale matched filtering method is adopted to extract the retinal vessels. Then, the gradient vector flow algorithm is introduced to locate the edge of the retinal vessels. Finally, we combine the results of matched filtering method and gradient vector flow algorithm to extract the vessels at different likelihood levels. The experiments demonstrate that our algorithm is efficient and the intensities of vessel images exactly represent the likelihood of the vessels.

Paper Details

Date Published: 27 October 2013
PDF: 7 pages
Proc. SPIE 8920, MIPPR 2013: Parallel Processing of Images and Optimization and Medical Imaging Processing, 89200H (27 October 2013); doi: 10.1117/12.2030264
Show Author Affiliations
Lei Yu, Changchun Institute of Optics, Fine Mechanics and Physics (China)
Suzhou Institute of Biomedical Engineering and Technology (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Mingliang Xia, Suzhou Institute of Biomedical Engineering and Technology (China)
Li Xuan, Changchun Institute of Optics, Fine Mechanics and Physics (China)


Published in SPIE Proceedings Vol. 8920:
MIPPR 2013: Parallel Processing of Images and Optimization and Medical Imaging Processing
Jianguo Liu, Editor(s)

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