VISUALIZATION OF QUANTITATIVE MODELING OF GLAUCOMA IN MULTIMODAL IMAGE ACQUISITION

Visualization is imperative for any living being. There are multiple reasons which lead to permanent vision loss. Glaucoma is one such eye disease which affects the perception of the individual. It is a degenerative, asymptomatic and irrevocable eye disease. Its advancement can be deferred by appropriate medical assessment at initial period. But far less Glaucoma is an enduring eye ailment which disturbs the optic nerve head of the retina due to intensification of intra ocular pressure (IOP) and consequence is damage to the visualization function of the individual. Wakefulness among the general public exists towards glaucoma and proportionately, number of people recognized is not as much related with affected. The existence of it can be identified by the vertical cup to disc ratio parameter obtained from the optic nerve head in fundus image. This paper proposes an algorithm which uses K-means clustering technique to segment the parameters, and a Graphical user interface has been designed using MATLAB 2018a. The simulated outcomes classify the fundus image as normal or glaucoma suspected and its effectiveness is confirmed with ophthalmologist upshots.