An Efficient Deep Intelligent Based MACO-CNN Algorithm for Classification of Diabetic Retinopathy Disease from Retinal Fundus Images

Abstract

Diabetic Retinopathy is a common microvascular complication in the retina of the eye due to the cause of Diabetes Mellitus. In this paper, we proposed Deep learning-based MACO-CNN algorithmfor the detection and classification of DR stages using retinal fundus images.This model is trained with a publically available dataset called Kaggle. Here we are using an implementation of GPU accelerated these networks to automatically diagnose and thereby classify high-resolution retinal images into 5 stages of the disease based on severity levels.Experimental results have showed that MACO-CNN outperforms other existing methodologies based on Accuracy, Precision, Recall and F-measure.