ABSTRACT
Computer Aided Diagnosis (CAD), which can automate the detection process for glaucoma, has attracted extensive attention from clinicians and researchers too. It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients and saving patients sight.
In this chapter, a review of the influential and exciting works that are related to this research based on glaucoma risk factors mentioned in (Chapter two), optic disc and optic cup segmentation methods, Disc to Cup Ratio (CDR), RNFL Review, Comparison between different segmentation methods, Comparison between different features types used to detect glaucoma from digital fundus images, and the existing computerized approaches in literature.
