A Deep Learning Based Method for Vitreous Hemorrhage Recognition in Fundoscopic Images

Diabetes Mellitus (DM) is a disease that affects millions of individuals globally. Diabetic Retinopathy (DR) is one of the many symptoms associated with Diabetes Mellitus. Diabetic Retinopathy occurs when chronic high glucose levels damage blood vessels within the eye, causing blood vessels to leak and in later stages cause Vitreous Hemorrhage. The key to preventing and treating advanced stages of Diabetic Retinopathy is early diagnosis. This paper introduces a method of training and boosting Deep Learning models for segmentation of Vitreous Hemorrhage in fundoscopic images, which would further facilitate classification of DR stages. The proposed algorithm generates a mask of Vitreous Hemorrhage by deploying pixel-wise binary classification to the fundoscopic images.