Retina Vessel Detection Using Fuzzy Ant Colony Algorithm

Author

Hooshyar, Sina ; Khayati, Rasoul

Author_Institution

Dept. of Biomed. Eng., Shahed Univ., Tehran, Iran

fYear

2010

fDate

May 31 2010-June 2 2010

Firstpage

239

Lastpage

244

Abstract

Vessel extraction in retina images is a primary and important step in studying diseases including vasculature changes. In this paper, a fuzzy clustering method based on Ant Colony Algorithm, inspired by food-searching natural behavior of ants, is described. Features of color retina images are extracted by eigenvalues analysis of Hessian matrix and Gabor filter bank. Artificial ants in the image use these features for searching and clustering processes. Experiments and results of proposed algorithm show its good performance in vessel extraction. This algorithm is tested on DRIVE database and its results are compared with other works using the same database. The accuracy of our method is 0.933 versus 0.947 for a second observer.

Keywords

Gabor filters; Hessian matrices; blood vessels; eye; image recognition; medical image processing; optimisation; pattern clustering; DRIVE database; Gabor filter bank; Hessian matrix; color retina image features; eigenvalues analysis; food-searching ant natural behavior; fuzzy ant colony algorithm; fuzzy clustering method; retina vessel detection; vasculature changes; vessel extraction; Clustering algorithms; Clustering methods; Diseases; Eigenvalues and eigenfunctions; Gabor filters; Image analysis; Image color analysis; Image databases; Retina; Spatial databases; Ant Colony Algorithm; Fuzzy Clustering; Gabor Filter Bank; Hessian Matrix; Retina Image;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Robot Vision (CRV), 2010 Canadian Conference on

Conference_Location

Ottawa, ON

Print_ISBN

978-1-4244-6963-5

Type

conf

DOI

10.1109/CRV.2010.38

Filename

5479181