Retinal vessel segmentation using Gabor filter and artificial neural network

Author

Nandy, Mahua ; Banerjee, M.

Author_Institution

MCKV Inst. of Eng., Kolkata, India

fYear

2012

fDate

Nov. 30 2012-Dec. 1 2012

Firstpage

157

Lastpage

160

Abstract

This paper demonstrates an automated segmentation scheme of retinal vasculature using Gabor filter bank, which is optimized on the basis of entropy. Different distributions of filter responses are encoded into features and the vasculature of normal and abnormal retina are segmented by artificial neural network(ANN). The training set of labeled pixels is obtained from the ground truth images of DRIVE database. The Receiver Operating Characteristics (ROC) in both abnormal and normal cases shows 96.16% accuracy.

Keywords

Gabor filters; channel bank filters; eye; image segmentation; medical image processing; neural nets; ANN; DRIVE database; Gabor filter bank; ROC; abnormal retina segmentation; artificial neural network; automated segmentation scheme; entropy; filter response distribution; labeled pixel training set; receiver operating characteristics; retinal vasculature; retinal vessel segmentation; ANN; Gabor filter; entropy; spectral flatness measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Applications of Information Technology (EAIT), 2012 Third International Conference on

Conference_Location

Kolkata

Print_ISBN

978-1-4673-1828-0

Type

conf

DOI

10.1109/EAIT.2012.6407885

Filename

6407885

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=589696