Classification of a Retinal Disease based on Different Supervised Learning Techniques

Amey Samant¹ , Sushma Kadge²

¹ Department of Electronics Engineering, K.J.Somaiya College of Engineering, Vidyavihar, Mumbai.
² Department of Electronics Engineering, K.J.Somaiya College of Engineering, Vidyavihar, Mumbai.

Correspondence should be addressed to: a.samant@somaiya.edu.

Section:Research Paper, Product Type: Journal
Vol.5 , Issue.3 , pp.9-13, Jun-2017

Online published on Jun 30, 2017

Copyright © Amey Samant, Sushma Kadge . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
This paper is based on classification of a retinal disease observed in premature infants named as “Retinopathy of Prematurity� (ROP). According to current market survey very few hospitals are associated in dealing with this disorder and is costly. So, the main aim here is to provide a simple yet effective MATLAB based algorithm for detection and classification of this disease. Here for computational purpose authors have used 30 affected and 30 normal images. These images are pre-processed using various MATLAB functions and commands and blood vessels are extracted. Later the tortuosity of these vessels is estimated and stored. These signals are further given to supervised learning classifiers, accuracy and error rate of the algorithm is estimated using different kernels.

Key-Words / Index Term :
Premature, infants, Retinopathy of Prematurity, Supervised Learning, Tortuosity

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