Promote Retinal Lesion Detection for Diabetic Retinopathy Stage Classification

Diabetes Mellitus (DM) is a health issue which is characterized by an elevated glucose level in the bloodstream. Diabetic Retinopathy (DR) stage classification plays an important role in diagnosis of patient for Diabetes Mellitus (DM). Different DR stages could normally be distinguished by various retinal lesions. In this work, Convolutional Neural Network (CNN) based retinal lesion detection method has been deployed to recognize microaneurysms (MAs) and hard exudates (HEs) in fundoscopic images in order to further facilitate DR stage classification. The proposed approach has achieved significant accuracy performance increase compared to the previous methods in DR stage classification.