Segmentational color map analysis to identify retinal detachment

Abstract

Abstract The recent perilous times entails the importance of good health for humans. This can be pertaining the maintenance of good health in various organs of the human body. With the increase of digital platforms, and the necessity to stay longer hours with gadgets and electronic devices, the human eye takes a toll in terms of absorbing radiations that maybe harmful. An imperative check of the eye is essential from time to time, as the luminous membrane that aids in vision needs to hold firm to the various components within itself. Although there are various treatments associated with the detection of eye detriments, several gremlins tend to loom at large. These eye diseases can arise from numerous reasons ranging from genetic disorders to accidents and vision loss due to stimulated injuries, infections and dysfunctional development of tissues/cells/nerves within the eye. Retinal detachment (RD) is one of the profound problems that persist amongst many individuals scaling over a diverse range of ages. The risk in relevance to untreated detachment of the eye leads to purblind and sometimes complete loss of vision. The previous paper concerning retinal detachment of human eye has focused on various algorithmic and post-processing approaches, but failed to identify the origination and symptoms that could aid in meticulous diagnosis. The indagation in this paper pivots on the unsheathing of attributes that explicates the disassociation of the retina from the underlying layers of the eye using the fundus image with cost-effectiveness and swifter analysis. An important characteristic that is emphasized in this study is the segmentation of eye floaters in the vitreous fluid of the eye. These eye floaters are color mapped to identify the presence of detached tissues in the eye. The histogram analysis using the grayscale thresholding value further aids in providing a detailed distinction of the normal eye from the detached eye. The simulations are carried out in MATLAB, and the results have been obtained successfully.