病态的
背景(考古学)
眼底(子宫)
验光服务
人工智能
视网膜
失明
计算机视觉
计算机科学
眼科
医学
病理
生物
古生物学
作者
Jiang Liu,Damon Wing Kee Wong,Joo‐Hwee Lim,Ngan Meng Tan,Zhuo Zhang,Huiqi Li,Fengshou Yin,Beng Hai Lee,Seang Mei Saw,Louis Tong,Tien Yin Wong
标识
DOI:10.1260/2040-2295.1.1.1
摘要
Pathological myopia is the seventh leading cause of blindness worldwide. Current methods for the detection of pathological myopia are manual and subjective. We have developed a system known as PAMELA (Pathological Myopia Detection Through Peripapillary Atrophy) to automatically assess a retinal fundus image for pathological myopia. This paper focuses on the texture analysis component of PAMELA which uses texture features, clinical image context and support vector machine-based classification to detect the presence of pathological myopia in a retinal fundus image. Results on a test image set from the Singapore Eye Research Institute show an accuracy of 87.5% and a sensitivity and specificity of 0.85 and 0.90 respectively. The results show good promise for PAMELA to be developed as an automatic tool for pathological myopia detection.
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