Retinal nerve fiber layer detection at optical coherence tomography image for the diagnosis of glaucoma

In this study, electrophysiological tests of the pelvis and the resulting signals were investigated using computer software. Clinical electrophysiological tests are tests that have an important place in ophthalmology and neuroophthalmology, which allows them to be evaluated as a whole. One of these tests Optical Coherence Tomography (OCT) is discussed. OCT is a medical imaging method that displays tomographic layers of the eye by taking tomographic sections at high resolution micron level. It is used for retinal diseases and glaucoma detection. Glaucomatous disease is a chronic optic neuropathy, which is accompanied by an increase in intraocular pressure, retinal ganglion cell degeneration, loss of visual field at the optic nerve head. Glaucoma is the world's leading cause of irreversible and preventable blindness. The Matlab program, in which the Retinal Nerve Fiber layer (RNFL) thickens and thickens for the detection of glaucoma, is used with image processing methods. Images of 20 patients from OCT were taken. With image processing techniques, the three-dimensional image, which is colored first, is turned into a two-dimensional gray image, thus facilitating operation. Canny, Sobel, and Gaussian filters, which are edge detection methods, have been tested. The Sobel filter is the best result. Layers are drawn by determining the neighborhoods from the points on the image. The top layer RNFL layer, which is important for glaucomatous disease, is colored from the obtained layers as a result of the studies made so as to make it visible on the OCT image.