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Detection of Retinal Disease in Diabetic Patients usingDeep Learning

Diabetic Retinopathy is also known as diabetic eye disease. There is an occurrence of damage to the retina when the person has diabetic Mellitus. Since manual scanning is difficult, an automatic screening test is performed for this disease. On comparing with other methods, Deep learning (DL) calculations are more efficient to calculate enormous volumes of data. This research study utilizes a new methodology called Back Propagation Neural Network (BPNN) to detect the disease and compare its efficiency with the existing and earlier methods, which are used for the detection of retinal disease. Allretinal pictures were handled, and deduced information elements, for example, vein width and convolution were semi- consequently extricated. A further developed BPNN with deduced information was created. Here a neural network is used to find the characteristics of diabetic fundus images. In addition to this, the type of diabetics can also be determined.