Detection of Hard Exudates in Retinal Fundus Images Using Deep Learning

Abstract

Diabetic Retinopathy (DR) is a retinal disorder that affects the people having diabetes mellitus for a long time (20 years). DR is one of the main reasons for the preventable blindness all over the world. If not detected early, the patient may progress to severe stages of irreversible blindness. Lack of Ophthalmologists poses a serious problem for the growing diabetes patients. It is advised to develop an automated DR screening system to assist the Ophthalmologist in decision making. Hard exudates develop when DR is present. It is important to detect hard exudates in order to detect DR in an early stage. Research has been done to detect hard exudates using regular image processing techniques and Machine Learning techniques. Here, a deep learning algorithm has been presented in this paper that detects hard exudates in fundus images of the retina.

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“…EXs are lipid deposits that remain after the gradual absorption of extravasated plasma substances due to abnormal permeability of the retinal capillary walls. Typically, EXs manifest as yellow-white or white spots or patches with clear boundaries [3,4]. SEs are a result of occlusion and damage to retinal microvessels, causing severe ischemia and hypoxia in the nourished tissue.…”

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“…The proposed algorithm and this research can be quite useful in DR Examination information for clinical ophthalmologists. Avula Benjamin et al [15] The Tensorflow deep learning framework was used to create the deep learning model presented in this study. The deep learning model built in this study was used to detect hard exudates present in the DR DRimpacted due picture.…”