Detection of Artery/Vein in Retinal Images Using CNN and GCN for Diagnosis of Hypertensive Retinopathy

A progressive disease of the retina known as hypertensive retinopathy (HR) is linked to both high blood pressure and diabetes mellitus. The severity and persistence of high blood pressure are directly connected with the development of HR. The results of the HR include constricted arterioles, retinal hemorrhage, macular edema, and cotton-like patches as symptoms of eye pathological problems. In this paper, a novel strategy that combines convolutional neural network (CNN) and graph convolutional network (GCN) is proposed to improve the accuracy of categorizing retinal blood vessels and classification of HR phases. The process is extracting vessel features from the spatial domain and representing them using graphs.