Diagnosis and Automatic Detection of Glaucoma Diseases for RNFL Affected Human Eyes

Abstract

Glaucoma is a quiet criminal of sight which is portrayed by raised intraocular pressure, slow vision misfortune that prompts lasting visual deficiency. Even though the infection is hopeless yet its side effects can be limited subsequently early discovery of the sickness is basic. It is an extravagant cycle to recognize the infection utilizing the cutting edge instruments because of which we are building up a strategy for discovery with the end goal that it is moderate by all the areas of the general public, likewise it very well may be identified at the beginning phase and counteraction can be taken. Henceforth, proposing some novel philosophies for glaucoma location by creating programming calculations in Matlab, which centers around the computerized discovery of glaucoma from fundus pictures utilizing the RNFL and different boundaries, and so on… ?. Glaucoma could be pigmentary, neo-vascular, neo-natal, congenital type. Hybrid algos could be used for detection purposes, in the sense for segmentation-2 methods could be merged, for feature extraction-2 methods could be merged, for image enhancement-2 methods can be merged, for classification-2 methods can be merged, like that & so on. We use the concepts of AI ML DL such as supervised learning, unsupervised learning, reinforcement learning, imitation learning, and multi-agent learning for training purposes and finally detect the disease in human beings with utmost accuracy. Matlab is the tool that is going to be used for simulation purposes. The work that is going to be considered in this report will be just a simulation case developed in the Matlab environment. The same can be thought of as developing a model in the Simulink environment, running the developed model & observing the results.