An automated glaucoma screening system using cup-to-disc ratio via Simple Linear Iterative Clustering superpixel approach

Publication date: August 2019Source: Biomedical Signal Processing and Control, Volume 53Author(s): Nur Ayuni Mohamed, Mohd Asyraf Zulkifley, Wan Mimi Diyana Wan Zaki, Aini HussainAbstractGlaucoma is an ocular disease caused by damaged optic nerve head (ONH) due to high intraocular pressure (IOP) within the eyeball. Usually, glaucoma patients will not realize the presence of this disease due to lack of visible early symptoms such as pain and redness mark. The disease can cause permanent blindness if it is not treated immediately. Hence, glaucoma screening is very crucial in detecting the disease during the early stages. There are various types of glaucoma screening tests such as tonometry test which is based on IOP measurement, ophthalmology test which is based on shape and color of the eyes, and pachymetry test which is based on complete field vision measurement. All these three screening tests involve manual assessment which is time-consuming and costly. Therefore, an efficient glaucoma screening system that can automatically analyze the severity level of the disease is very much needed. Thus, the main objective of this paper is to develop an automatic glaucoma screening system based on superpixel classification by providing a high-quality input image. Firstly, input images are undergone preprocessing methods to cater for noise removal and illumination correction. This is emphasized in the implementation of the anisotropic diffusion filter and illumination correction method....
Source: Biomedical Signal Processing and Control - Category: Biomedical Science Source Type: research