Improved Glaucoma Diagnosis Using Deep Learning

Abstract

Glaucoma is termed as one of the top leading causes of vision loss and in many cases is irreversible [1]. It is a condition that damages the optic nerve and it goes unnoticed in early stages as the symptoms are not prominent in the early stages. Recent approaches have been made to automate the detection of glaucoma based on available datasets. World Health Organization also looks at eye defects to be critical as a result of the health evaluation conducted globally on health challenges. Survey points to the fact that it can become one of the primary concerns in 2020 which might affect around 75-80 million people. We have automated the process of diagnosis of glaucoma using deep learning approaches. Image processing has gained a lot of attraction and can be used for this problem in forming a computer-aided diagnosis for diseases. In the end, we have compared our results with previous approaches, which shows that our method has a better accuracy score.