Diabetic Retinopathy: An Overview on Pathophysiology, Diagnosis and Recent Advances in the Treatment

Diabetic Retinopathy (DR) is the condition caused due to uncontrolled diabetes that can lead to vision impairment. It greatly affects the retinal blood vessels and diminishes the fundus light-sensitive inner coating. Early diagnosis and regular screening of this disease are essential for prompt processing through artificial intelligence techniques. This paper targets assessing the latest techniques for screening and diagnosing DR, including 94 articles based on the Detection and grading of DR. Diabetic retinopathy, a leading cause of vision loss in working-age adults, is a complication of diabetes mellitus where damage to the retina’s blood vessels occurs, potentially leading to blindness if left untreated. Diabetic retinopathy the most frequently occurring complication of diabetes mellitus and remains a leading cause of vision loss globally. The manual diagnosis process of DR retina fundus images by ophthalmologists is time-, effort, and cost-consuming and prone to misdiagnosis unlike computer-aided diagnosis systems. Recently, deep learning has become one of the most common techniques that has achieved better performance in many areas, especially in medical image analysis and classification. Variation in compliance rates, age of onset of diabetes, glycaemic control and screening sensitivities influence the cost-effectiveness of screening programmes and are important sources of uncertainty in relation to the issue of optimal screening intervals.