Hybrid Retinal Image Enhancement Algorithm for Diabetic Retinopathy Diagnostic Using Deep Learning Model

Diabetic Retinopathy (DR) is a prevalent acute stage of diabetes mellitus that causes vision-effecting abnormalities on the retina. This will cause blindness if not identified early. Because DR an irreversible procedure, and only vision preserved via care. Consequently, Early diagnosis care with significantly minimize chance loss. In modern ophthalmology, retinal image analysis has become popular approach to disease diagnosis. The ophthalmologists computerized systems extensively employ fundus angiography detect DR-based clinical signs for early detection DR. photographs are commonly prone low contrast, noise, irregular illumination issues due complexity imaging environments such as variety angles light conditions. research presents Algorithm improving quality images strengthen standard color by reducing noise contrast. includes two main stages: cropping remove insignificant content, then applying shape crop gaussian blurring reduction contrast improvement. experimental results evaluated using datasets EyePACS MESSIDOR. It’s clearly shown outcomes feature extraction classification enhanced outperform without enhancement approach. improved algorithm also tested in smart hospitals IoMT application.