Inventive Methodology on "Diabetic Retinopathy Detection Using Molecular Segmentation in Convolution Neural Network"

Diabetic patients risk being blind because their pancreas does not produce enough insulin. Diabetic retinopathy gradually impairs a patient's vision as the disease progresses. To understand how diabetes affects the eye, retinal images captured with a fundal camera may be helpful. This study aims to detect blood vessels, identify haemorrhages, and classify diabetic retinopathy into different phases of  diabetic retinopathy into normal, mild, and (NPDR) non-proliferative diabetic retinopathy .Classifying the various stages of diabetes-related retinopathy begins with a retinal picture. Using the contrast between the blood vessels and the surroundings, the retinal vascular network can be segmented. The method's intelligence contributes to the process of generating more accurate, convenient, and faster results.