Automatic Detection of Glaucoma Using Optical Coherence Tomography Image

Glaucoma is an eye disorder in which the optic nerve suffers damage, leading to vision defect in the affected eye(s) and rolling to complete blindness if untreated. It is frequently associated with increased pressure in the fluid of the eye; aqueous humour. Glaucoma often goes undetected until significant damage to the subject’s visual field has occurred. As glaucoma progresses, neural tissues die, the nerve fiber layer thins and the cup-to-disk ratio increases. The conventional techniques typically used for this measurement are unreliable and creates intricacies while measuring considerably small changes in the nerve head geometry. In this study, an algorithm is proposed that facilitates segmentation of the retinal-nerve head vitreal boundary, choroid-nerve head boundary identification and determination of the extent of the optic cup and disk. This algorithm is assessed and evaluated with many samples of OCT images from both normal and pathological eyes. Subsequently, the results are validated with the available documents from expert ophthalmologist reporting the correlation coefficient for cup to disk ratio.