DocumentCode :
3275660
Title :
Retinal Vascular Image Segmentation Using Genetic Algorithm Plus FCM Clustering
Author :
Songhua Xie ; Hui Nie
Author_Institution :
Sch. of Sci., Wuhan Univ. of Technol., Wuhan, China
fYear :
2013
fDate :
16-18 Jan. 2013
Firstpage :
1225
Lastpage :
1228
Abstract :
Those retinal vascular image without regular background and fixed contrast, make conventional approaches hard to achieve a satisfactory partition. So this paper presents a novel segmentation algorithm -- combination of genetic algorithms and FCM fuzzy clustering algorithms. First genetic algorithm is used to obtain the approximate solution of the global optimal solution. Then the approximate solution is used as the initial value of the FCM algorithm, FCM algorithm further is used for global optimum. Experimental results show that the algorithm is effective in performing retinal vascular image segmentation using morphological filtering.
Keywords :
biomedical optical imaging; blood vessels; eye; filtering theory; fuzzy set theory; genetic algorithms; image colour analysis; image segmentation; medical image processing; pattern clustering; FCM fuzzy clustering algorithms; genetic algorithm; global optimal solution; image color analysis; morphological filtering; retinal vascular image segmentation; satisfactory partition; Approximation algorithms; Clustering algorithms; Filtering; Genetic algorithms; Genetics; Image segmentation; Retina; Fuzzy C-Means Clustering; Genetic Algorithm; Image Segmentation; Retinal Vascular;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
Type :
conf
DOI :
10.1109/ISDEA.2012.289
Filename :
6455993
Link To Document :
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