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All Journal Indonesian Journal of Electrical Engineering and Computer Science
R. K. Bathla
Desh Bhagat University

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A review on supervised learning methodologies for detection of exudates in diabetic retinopathy Ujwala W. Wasekar; R. K. Bathla
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp837-846

Abstract

Diabetic retinopathy has become one of the major reasons for blindness in the world. Early and precise diagnosis of the disease may save one’s eyesight from irreversible damage. Manual detection of lesions is time consuming and may not be as accurate as desirable. Many automated systems have been developed recently to help ophthalmologists in their endeavors. Exudates are one of the early signs of manifestation of diabetic retinopathy. In this paper, the methodologies detecting exudates in retinal fundus images were reviewed. These methods were categorized into deep learning, machine learning and methods primarily focusing on image processing techniques. The comprehensive view of the performances of the methods was given. Several datasets were described briefly. Most of the researchers preferred combination of multiple publically available databases. Also, the potential areas of research were discussed. It was found that sensitivity which identifies the abnormal images correctly, is the most widely used performance measure. The study will be helpful to the researchers wanting to explore more in this field.
Co-Authors Ujwala W. Wasekar