Machine Learning Techniques for Diabetic Retinopathy Detection and Classification: A Survey

Abstract

Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes mellitus and a major cause of visual impairment worldwide. Early detection and treatment is essential to avoid permanent blindness. However, early diagnosis is often quite challenging and requires the service of an expert ophthalmologist. Recently, machine learning algorithms have achieved better performance in medical image analysis and disease diagnosis. This article presents a review of research papers on the application of machine learning algorithms in DR detection and classification. Furthermore, the paper reviews available datasets and also discuss the challenges that provide new research insights.

Keywords: Diabetic retinopathy, microaneurysms, deep neural networks,  disease classification

      Paper Type: Review Paper