A Review on Diabetic Retinopathy Detection Methods

Abstract

Diabetes mellitus frequently results in diabetic retinopathy (DR), which results in lesions on the eye that impair vision. Blindness may result if it is not caught in time. Unfortunately, there is no cure for DR; treatment only preserves eyesight. Early diagnosis and treatment of DR can greatly lower the chance of vision loss. In contrast to computer-aided diagnosis methods, the manual diagnosis of DR retinal fundus images by ophthalmologists is time-, effort-, and cost-consuming as well as prone to error. Recently, deep learning has become one of the most common techniques that has improved performance in many areas, especially medical image analysis and classification. Convolutional neural networks are more frequently employed as a deep learning technique in the study of medical images, and they are very successful. In this paper, state-of-the-art techniques for deep learning-based detection and classification of DR color fundus images have been reviewed.