Optimized Deep Learning Architecture for Precise Segmentation and Early Diagnosis of Diabetic Retinopathy

Diabetic Retinopathy (DR) is a primary cause of vision impairment in individuals with diabetes, necessitating early and precise detection for prompt treatments. Diabetic Retinopathy represents a widening and serious hazard to world sight, arising from injury to retinal blood vessels that follows extended periods of high blood glucose. Given the expected rise in diabetes prevalence, the urgent priority is to create powerful, automated systems that can spot DR in its earliest, most treatable stages, thereby reducing the chance of blindness and enhancing the quality of life for patients. Since the vision loss linked to DR is largely avoidable, our focus must rest on timely identification and prompt treatment, possible only with the latest advances in screening and analytical technologies.