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Research Journal of Pharmacy and Technology
Year : 2015, Volume : 8, Issue : 9
First page : ( 1284) Last page : ( 1288)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2015.00233.4

Automated Diagnosis of Age Related Macular degeneration from fundus image

Narasimhan K.1,*, Dr. Vijayarekha K.2

1Assistant Professor, SASTRA University, Thirumalaisamudhram, Thanjavur, Tamilnadu, India

2Associate Dean, School of EEE, SASTRA University, Thirumalaisamudhram, Thanjavur, Tamilnadu, India

*Corresponding Author E-mail: knr@ece.sastra.edu

Online published on 28 October, 2015.

Abstract

Retinal image analysis paves the way for easy diagnosis of retinal pathologies and acts as a first aid tool for ophthalmologist. In this paper a novel approach has been proposed for the automated diagnosis of age related macular degeneration (AMD) from fundus image. A landmark called Drusen, in fundus image whose detection and its location identification play the crucial to detect and grade AMD. In pre-processing step optic disk and blood vessels are detected and removed. By applying log Gabor filter to the pre-processed image energy has been computed. Gray level co-occurrence matrix has been calculated for the image and after applying fuzzy entropy thresholding technique, two discriminative features auto correlation and contrast features have been chosen. Classification is done by using a total of three feature vector using k-nearest neighbour, Support Vector Machine, Random forest classifier. Highest sensitivity is obtained in the case of Random forest classifier. SVM with RBF kernel also does better classification next to random forest.

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Keywords

Age Related Macular Degeneration (AMD), Drusen, Log gabor filter, knn, SVM, Random Forest.

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