Glaucoma Detection using GAN-based Domain Adaptation Approach

A GAN- based Domain Adaptation Method for Glaucoma Diagnosis aims to detect the Glaucoma disease based on GAN method. GAN is a deep learning method comprised of generator and discriminator. The optic nerve of the eye is continuously injured in Glaucoma, an untreatable eye illness. It causes the retina’s gradual, cumulative deterioration. Even while it cannot be completely treated, the progression can be stopped by early identification. The Optic Head Nerve is impacted by glaucoma, and the density of this nerve depends on the depth of the Optic Cup plus Optic Disc. This research study creates a model where glaucoma is only detectable in the early stages, preventing additional vision loss. Here, several test, train, and validation images are considered and that will be enhanced before being sent on to the next step in the process. The Convolutional Neural Network (CNN) algorithm and other Deep Learning (DL) algorithms are utilized to forecast the glaucoma disease. The proposed system is implemented on Google Colab.