Glaucoma Identification on Fundus Retinal Images Using Statistical Modelling Approach

9th Annual Basic Science International Conference 2019

自然科学（总论）

Anwar, A.E.^1 ; Chamidah, N.^2

Department of Mathematics, Airlangga University, Surabaya, Indonesia^1

Department of Mathematics, Faculty of Science and Technology, Airlangga University, Surabaya, Indonesia^2

关键词: After cataract;    Classification accuracy;    Eye disease;    Mathematical computation;    Optic nerve head;    Penalized splines;    Retinal image;    Statistical modelling;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/546/5/052010/pdf
DOI  :  10.1088/1757-899X/546/5/052010

学科分类：自然科学（综合）

来源: IOP

【 摘 要 】

Glaucoma is an eye disease characterized by progressive deterioration of the optic nerve head and a broad view that can cause blindness. The Population Based Survey in 2010 indicates that glaucoma was the second leading cause of blindness after cataracts, which was about 8% of 36 million sufferers of blindness worldwide. Symptoms of glaucoma that arise usually cannot be felt directly. So it is necessary to do an eye examination to find out glaucoma, one of which is to look at the size of the optic disk in the digital fundus photo. The previous studies about glaucoma identification were done by using mathematical computation approach that have still not satisfied. Therefore, in this study we propose a new method, i.e., statistical modelling approach to identify glaucoma. In statistical modelling, there are two approaches, i.e., parametrical approach, and non-parametrical approach based on penalized spline estimator. The result of classification accuracy by using parametrical and non-parametrical approaches are 73.3% and 93.33%, respectively. Based on the result, we conclude that non-parametrical approach has better outcome so that it can be used to identify glaucoma on fundus retinal image.