DocumentCode :
2219650
Title :
Segmentation of retinal blood vessels using a novel clustering algorithm
Author :
Salem, Sameh A. ; Salem, Nancy M. ; Nandi, Asoke K.
Author_Institution :
Dept. of Electr. Eng. & Electron., Univ. of Liverpool, Liverpool, UK
fYear :
2006
fDate :
4-8 Sept. 2006
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, segmentation of blood vessels from colour retinal images using a novel clustering algorithm and scale-space features is proposed. The proposed clustering algorithm, which we call Nearest Neighbour Clustering Algorithm (NNCA), uses the same concept as the K-nearest neighbour (KNN) classifier with the advantage that the algorithm needs no training set and it is completely unsupervised. Results from the proposed clustering algorithm are comparable with the KNN classifier, which does require training set.
Keywords :
blood vessels; eye; image classification; image segmentation; medical image processing; pattern clustering; statistical analysis; KNN classifier; colour retinal image; k-nearest neighbour; nearest neighbour clustering algorithm; retinal blood vessel segmentation; scale-space feature; Biomedical imaging; Blood vessels; Clustering algorithms; Image segmentation; Retina; Signal processing algorithms; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2006 14th European
Conference_Location :
Florence
ISSN :
2219-5491
Type :
conf
Filename :
7071386
Link To Document :
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