Analysis Of Segmentation And Classification Techniques For Detection Of Glaucoma

Abstract

Medical image processing is a tool and technique for creating a visual image of inside of the body. The rapid advancement of digital imaging and computer vision has broadened the potential for the use of imaging technology in medicine. Image processing is especially useful in diagnostic medical systems. The retina, which is a layered tissue, lines inside of the eye to enable the incoming light to be converted to a neural signal that's processed further within the cortical area of the brain. Glaucoma analysis in the retinal fundus image is necessary to avoid loss of eyesight. The time of Glaucoma detection from retinal images is very critical for slowing down the adverse effect, since glaucoma can not be cured. Several studies have shown that glaucoma is detected or screened in a 2-D retinal  image. This paper discusses the various methods of segmentation  techniques used to diagnose retinal glaucoma based on the Cup to Disk Ratio (CDR) assessment of the pre-processed image. This paper discusses the assorted methods of segmentation techniques which are used to analyse retinal glaucoma by   Cup to Disk Ratio (CDR) assessment of the pre-processed image. the diagnosis of glaucoma using the features obtained from the image on the basis of the study of the adaptive thresholding technique. a neural signal that's processed further within the cortical area of the brain.