A Novel Approach to Glaucoma Screening using Computer Vision

Glaucoma is one of the major and critical eye diseases discovered till date. It is actually a group of diseases that damage the optic nerve and subsequently result in vision loss and blindness. One of the major causes of Glaucoma is the intrinsic distortion of the optic nerve resulting in high fluid pressure on the front portion of the eye. The primary objective of the paper is to classify High Resolution Fundus images of the retina into Glaucomatous and Non-Glaucomatous. In order to achieve that, a DL-ML Hybrid Model has been developed with an initial image processing. The overall methodology followed in this paper has been termed as N-S Model. The HRF (High Resolution Fundus) Image Database consisting of 30 images is used for the purpose. The N-S Model was deployed after development and clocked a 100% Validation Accuracy and Sensitivity of 1.0. Such an Intelligent System can accelerate the process of diagnosis and reduce the review of doctors.