A Review on Deep Learning Models for Optic Disc Segmentation and Glaucoma Classification

Abstract

Due to the recent existence of large datasets and advancements in processing capabilities, deep learning has risen to the forefront of artificial intelligence on a variety of tasks, particularly those related to image classification and pattern recognition. Ophthalmology offers a chance to see how deep learning classifiers are used in medicine. Globally, glaucoma is the prime factor of chronic blindness and disability. Despite this, most patients are unsure whether they have glaucoma, and detecting glaucoma progression with present technology is challenging in clinical practice. We can detect glaucoma early with the help of deep learning technology. The segmentation of the optic disc and classification of glaucoma using retinal data will be examined using several deep structured learning approaches in this research. Also presented a basic understanding of deep learning. Finally, the difficulties that deep learning models face are highlighted.