Computerized Diagnosis of Diabetic Retinopathy based on Deep Learning Techniques
Birlin T Monisha, C. Divya, N. Muthukumaran
Abstract
Diabetic Retinopathy (DR) is a condition that is becoming increasingly prevalent across the world. DR is an eye problem that develops as a result of a high glucose level in the blood, which destroys the retina, which is located in the back of the eye, causing vision loss. Type II diabetes (T2D) can develop in a person who has Type I diabetes (T1D) for more than six years. T2D with impaired vision is a sign of Diabetic Retinopathy, which is a serious eye condition (DR). Patients with diabetes in their childhood or adolescence are at risk of developing health problems throughout their life. The loss of eyesight caused by DR is irreversible once it occurs. Early diagnosis of diabetic retinopathy (DR) helps diabetic individuals avoid visual loss. In addition to being time-consuming and expensive, previous techniques of DR detection are prone to mistakes. The use of computerized diagnostics for DR eliminates all of the difficulties associated with older techniques. The authors of this review study provided a thorough understanding of the present approaches for the automatic detection of DR, as well as the problems associated with improving overall performance.