Research on Deep Learning in the Detection and Classification of Diabetic Retinopathy

Diabetic retinopathy is so imperceptible in its early stages that it can lead to blindness if it is not treated at the right time. If early and timely intervention, it will reduce visual impairment. Color doppler ultrasound imaging, fundus photography, Optical Tomography and Fundus Fluorescein angiography are commonly used in the diagnosis and treatment of diabetic retinopathy. Recently, deep learning techniques have been developed to assist in the early screening and diagnosis of diabetic retinas on a large scale. This article mainly introduces the research value and significance of deep learning in diabetic retina. In this paper, some deep learning and traditional machine learning methods for diabetic retinal image detection and severity classification are summarized, and some unresolved problems and prospects are discussed.