Classification of Fundus Images Using Neural Network Approach

Abstract

Diabetic retinopathy (DR), which affects the blood vessels of the human retina, is considered to be the most serious complication prevalent among diabetic patients. If detected successfully at an early stage, the ophthalmologist would be able to treat the patients by advanced laser treatment to prevent total blindness. In this study, a technique based on morphological image processing and fuzzy logic to detect hard exudates from DR retinal images is explored. The proposed technique is to classify the eye by using a neural network approach (classifier) to predict whether it is affected or not. Here, a classifier is added before the fuzzy logic. This fuzzy will tell how much and where it is affected. The proposed technique will tell whether the eye is abnormal or normal.