Automated Detection of Glaucoma using Fundus Image: A Comprehensive Review

Glaucoma is an eye disease that gradually affects the optic nerve and may cause permanent loss of vision if it is not diagnosed and treated early. Ophthalmologists currently use several non-invasive imaging methods for glaucoma diagnosis, including Optical Coherence Tomography (OCT), Heidelberg Retinal Tomography (HRT), Scanning Laser Polarimetry, and color fundus imaging [4]. Although OCT, HRT, and Scanning Laser Polarimetry provide useful information for diagnosis and disease assessment, these techniques can be expensive and often require specialized equipment and experienced professionals. Fundus imaging is a comparatively simple and cost-effective alternative that can be used to examine important features of the optic nerve and retina. This has encouraged researchers to develop computer-based algorithms for the early and accurate detection of glaucoma from fundus images. Therefore, this paper presents a review of existing research methods and recent developments in glaucoma detection using fundus images.