Paper Info
Title
An Automatic Hybrid Method for Retinal Blood Vessel Extraction
Abstract
The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper presents a novel hybrid automatic approach for the extraction of retinal image vessels. The method consists in the application of mathematical morphology and a fuzzy clustering algorithm followed by a purification procedure. In mathematical morphology, the retinal image is smoothed and strengthened so that the blood vessels are enhanced and the background information is suppressed. The fuzzy clustering algorithm is then employed to the previous enhanced image for segmentation. After the fuzzy segmentation, a purification procedure is used to reduce the weak edges and noise, and the final results of the blood vessels are consequently achieved. The performance of the proposed method is compared with some existing segmentation methods and hand-labeled segmentations. The approach has been tested on a series of retinal images, and experimental results show that our technique is promising and effective.
Year
DOI
Venue
2008
10.2478/v10006-008-0036-5
Applied Mathematics and Computer Science
Keywords
Field
DocType
previous enhanced image,fuzzy clustering algorithm,retinal blood vessel extraction,hand-labeled segmentation,mathematical morphology,fuzzy clustering.,purification procedure,blood vessel extraction,retinal image,existing segmentation method,retinal image vessel,automatic hybrid method,fuzzy segmentation,blood vessel,fuzzy clustering
Computer vision,Fuzzy clustering,Mathematical morphology,Segmentation,Retinal image,Artificial intelligence,Retinal,Mathematics,Fuzzy segmentation,Blood vessel
Journal
Volume
Issue
ISSN
18
3
1641-876X
Citations 
PageRank 
References 
20
0.78
11
Authors
3
Name
Order
Citations
PageRank
Yong Yang112815.65
Shuying Huang213923.46
Nini Rao38511.36