Review of Automated Glaucoma Detection Techniques

Glaucoma, an eye disease, is often referred to as the silent thief of sight. The damage done by glaucoma is irreversible. Early detection and treatment of glaucoma is the only solution. Till date many works have been done towards automatic glaucoma detection using Color Fundus Images (CFI) and Optical Coherence Tomography (OCT) images by extracting structural features. Structural features can be extracted from optic nerve head (ONH) analysis in case of CFI and Retinal Layers (RL) analysis in OCT images for glaucoma assessment. But unfortunately, the works till date fall short of expected accuracy in this regard. A review of automated glaucoma detection techniques is presented in this paper. The paper also discusses various structural features that are relevant to CFI and OCT images respectively for automated glaucoma detection. The paper concludes that combining structural features from both CFI and OCT images would result in more accurate glaucoma assessment.