Abstract: Diabetic Retinopathy is a major disease that has affected over 290 million people globally and 69.2 million people in India, the rate of people getting affected will increase exponentially in the coming years. Diabetic Retinopathy is an ailment linked to the fundus of the eye and can have adverse effects on the patient, if at all left undiagnosed respectively.
Our project aims to construct a graphical user interface that can integrate image processing techniques together in order to predict whether the input fundus/retinal image received from the patient is affected with Diabetic Retinopathy or not; if affected, the graphical user interface will display the severity along with the required action needed to be undertaken by the user / patient. This essentially reduces the processing time involved in the process of detecting the disease and also the ophthalmologists can also have our graphical user interface as a backup that can be used for validating or assist in detecting the disease
Keywords: Diabetic Retinopathy, GUI, Convolutional Neural Network, Python.
| DOI: 10.17148/IJARCCE.2022.11482