Glaucoma Detection Using AI (original) (raw)

Glaucoma is a disease that affects the optic nerve. This disease, over a period of time, can lead to loss of vision. It is also known as 'silent thief of sight'. This is because this disease slowly damages the eye, and ultimately causes irreparable harm before any vision loss. There are several methods in which the disease can be treated, if detected at an early stage. It is definitely not possible for any technology, including artificial intelligence, to replace a doctor. However, it is possible to develop a model based on several classical image processing algorithms, combined with artificial intelligence that can detect onset of Glaucoma based on certain parameters of the retinal fundus. This model would play an important role in early detection of the disease and assist the doctor. The traditional methods to detect glaucoma, as efficient as they may be, are usually expensive. Here we propose a machine learning approach to diagnose from fundus images and accurately classify its severity. In this paper we propose Support Vector Machine (SVM) method to segregate, train the models using a high-end graphics processor unit (GPU) and augmented the hull convex approach to boost the accuracy of the image processing mechanisms along with distinguishing the different stages of glaucoma. Added to these, we have proposed a feasible web application for the screening process.