A Survey on Diabetic Retinopathy Disease Detection and Classification using Deep Learning Techniques
S. Valarmathi, R. Vijayabhanu
Abstract
Diabetes is the most commonly found chronic disease seen in many people of different age groups with poor insulin production, which causes high blood sugar. Diabetes, when left untreated, can lead to the development of several diseases across the body. Diabetic Retinopathy (DR) is an asymptomatic eye disease induced by diabetes that results in damaged retinal vessels. Many automatic diagnostic systems have been developed in the literature in which conventional handcrafted features were used. With the development of Deep Learning (DL), particularly in medical imaging, more accurate and potential results are produced, as it performs automatic feature extraction. Convolutional Neural Networks (CNNs) are the most widely used deep learning method in medical image analysis. In this paper, several Deep Learning-based diabetic retinopathy disease detection and classification techniques are analyzed and reviewed for better understanding.