An Artificial Intelligence Based Scheme for Automatic Detection of Diabetic Hypertensive Retinopathy in Fundus Images

Abstract

Diabetic Retinopathy (DR) is the major cause of blindness found in the person having diabetes. DR can be caused by diabetes mellitus that affects the retinal microvasculature. So, there is a need to detect DR in the early stages to reduce the risk of blindness in working-age groups. DR can be detected by taking the fundus images of the retina. Detection of morphological changes that include microaneurysms, hard exudates, soft exudates (cotton wool spot), hemorrhages, macula, optic disk, optic nerve head, and increase in the blood vessel in fundus images is still a tedious task. These morphological changes can be detected either by time-consuming manual inspection or by Computer-Aided Diagnosis (CAD) that can help the ophthalmologist to identify the problem. Hypertensive Retinopathy (HR) occurs due to hypertension (high blood pressure) resulting in affecting the blood vessels. The symptoms of HR initiates with AVR nicking, tortuosity, bifurcation in blood vessels in early detection of disease. newline