A system for the automatic detection of glaucoma using retinal images

Glaucoma is an optic neuropathy and it principal cause of blindness in the world. In this paper, a system able to treat and analyze the Visual Field (VF) images and Optical Coherence Tomography of the Ganglion Cell Layer (OCT-GCL) images is proposed, in order to help early detection of glaucoma in its early stages. The proposed approach is based on calculating the percentage of healthy, sick and dead regions of VF and OCT-GCL images. In order to carry out this calculation, we combined the thresholding methods with morphological operators and median filter to extract all regions. These algorithms developed were tested on a set of images of a local database composed of 58 OCT-GCL images and 21 VF images. The results obtained are satisfactory and confirmed by experts in ophthalmology.