CNN Classification of Multi-Scale Ensemble OCT for Macular Image Analysis

Abstract

Computer-Aided Diagnosis (CAD) of retinal pathology is a dynamic medical analysis area. The CAD system in the optical coherence tomography (OCT) is important for the monitoring of ocular diseases because of the heavy utilization of the retinal OCT imaging process. The Multi-Scale Expert Convolution Mixture (MCME) is designed to classify the normal retina. OCT is becoming one of the most popular non-invasive evaluation approaches for retinal eye disease. The amount of OCT is growing and the automation of OCT image analysis is becoming increasingly necessary. The surrogate-aided classification approach is to automatically classify retinal OCT images because of the Convolution Neural Network (CNN). The methods to classify OCT images and macular OCT classification are done by using CNN. Maculopathy is a combined collection of diseases to facilitate the effect of the inner region of the retina identified as the macula. Central Serous Choric Retinopathy (CSCR) and macular edema are the main two types of maculopathies. Numerous researches have focused on the detection of these macular disorders with OCT. It is used to overcome retinal diseases.