UNRAVELLING DIABETIC RETINOPATHY THROUGH IMAGE PROCESSING, NEURAL NETWORKS AND FUZZY LOGIC – A REVIEW


Srinivasan A, Sudha S

Abstract


One of the main causes of blindness is diabetic retinopathy (DR) and it may affect people of any ages. In these days, both young and old ages are affected by diabetes, and the di abetes is the main cause of DR. Hence, it is necessary to have an automated system with good accuracy and less computation time to diagnose and treat DR, and the automated system can simplify the work of ophthalmologists. The objective is to present an overview of various works recently in detecting and segmenting the various lesions of DR. Papers were categorized based on the diagnosing tools and the methods used for detecting early and advanced stage lesions. The early lesions of DR are microaneurysms, hemorrhages, exudates, and cotton wool spots and in the advanced stage, new and fragile blood vessels can be grown. Results have been evaluated in terms of sensitivity, specificity, accuracy and receiver operating characteristic curve. This paper analyzed the various steps and different algorithms used recently for the detection and classification of DR lesions. A comparison of performances has been made in terms of sensitivity, specificity, area under the curve, and accuracy. Suggestions, future work
and the area to be improved were also discussed.

Keywords: Diabetic retinopathy, Image processing, Morphological operations, Neural network, Fuzzy logic.

 


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About this article

Title

UNRAVELLING DIABETIC RETINOPATHY THROUGH IMAGE PROCESSING, NEURAL NETWORKS AND FUZZY LOGIC – A REVIEW

DOI

10.22159/ajpcr.2017.v10i4.17023

Date

01-04-2017

Additional Links

Manuscript Submission

Journal

Asian Journal of Pharmaceutical and Clinical Research
Vol 10 Issue 4 April 2017 Page: 32-37

Print ISSN

0974-2441

Online ISSN

2455-3891

Statistics

153 Views | 161 Downloads

Authors & Affiliations

Srinivasan A
Srinivasa Ramanujan Centre SASTRA University Kumbakonam 612001
India

Sudha S


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