Automated Techniques for Detection and Classification of Diabetic Macular Edema: A Review

Abstract

Diabetic Macular Edema is the main cause of vision loss in diabetic patients caused by the accumulation of fluid in the macular region of retina. Detecting it at an early stage is a herculean task and requires great expertise and consumption of time. Many automated techniques developed to do so were analyzed in this study. Moreover, a fine survey of preprocessing techniques, feature selection, feature extraction, Machine Learning (ML) techniques and the data sets used for its training and testing was conducted. Many automated techniques in that matter have been able to achieve high accuracy in detection as well as classification of DME. Optical Coherence Tomography (OCT) stands out to be more effective and better result yielding than others for the detection and classification of DME