Fundus image classification methods for the detection of glaucoma: A review

Abstract

Glaucoma is a neurodegenerative illness and is considered as a standout amongst the most widely recognized reasons for visual impairment. Nerve's degeneration is an irretrievable procedure, so the diagnosis of the illness at an early stage is an absolute requirement to stay away from lasting loss of vision. Glaucoma effected mainly because of increased intraocular pressure, if it is not distinguished and looked early, it can result in visual impairment. There are not generally evident side effects of glaucoma; thus, patients attempt to get treatment just when the seriousness of malady is advanced altogether. Determination of glaucoma often comprises of review of the basic crumbling of the nerve in conjunction with the examination of visual function capacity. This article shows the persistent illustration of glaucoma, its side effects, and the potential people inclined to this malady. The essence of this article is on different classification methods being utilized and proposed by various scientists for the identification of glaucoma. This article audits a few division and segmentation methodologies that are exceptionally useful for recognizable proof, identification, and diagnosis of glaucoma. The research related to the findings and the treatment is likewise evaluated in this article.