OPTIVISION: ENHANCING DIABETIC RETINOPATHY DETECTION USING DEEP LEARNING

Abstract

The diabetic retinopathy is an eye disease associated with chronic diabetes. It is the leading cause of blindness in people. Diabetic Retinopathy is complication of diabetes that targets the eyes by damaging the retinal blood vessels. Primarily occurs when the blood sugar level is unmanageable. Therefore the person with diabetes mellitus is always at a high risk of acquiring this disease. The present work considers a deep learning methodology specifically a convolution neural network which is applied for the early detection of diabetic retinopathy is detected on time. It classifies the fundus images based n its severity levels as N0 DR, and Yes DR. The main objective of this work is t build a stable and noise compatible system for detection of diabetic retinopathy. This work employs the deep learning methodology for detecting the diabetic retinopathy based on severity level. Many processes were carried out before feeding the images to the network. Key Words: Diabetic retinopathy detection, Deep learning, CNN, Real time classification. The diabetic retinopathy is an eye disease associated with chronic diabetes. It is the leading cause of blindness in people. Diabetic Retinopathy is complication of diabetes that targets the eyes by damaging the retinal blood vessels. Primarily occurs when the blood sugar level is unmanageable. Therefore the person with diabetes mellitus is always at a high risk of acquiring this disease. The present work considers a deep learning methodology specifically a convolution neural network which is applied for the early detection of diabetic retinopathy is detected on time. It classifies the fundus images based n its severity levels as N0 DR, and Yes DR. The main objective of this work is t build a stable and noise compatible system for detection of diabetic retinopathy. This work employs the deep learning methodology for detecting the diabetic retinopathy based on severity level. Many processes were carried out before feeding the images to the network. Key Words: Diabetic retinopathy detection, Deep learning, CNN, Real time classification.