期刊
MEDICAL IMAGE ANALYSIS
卷 14, 期 3, 页码 471-481出版社
ELSEVIER
DOI: 10.1016/j.media.2009.12.006
关键词
Computer aided diagnosis; Glaucoma; Optic disk; Appearance-based image analysis; Linear principal component analysis
类别
资金
- German National Science Foundation (DFG) [SFB 539 A4]
- German Academic Exchange Service (DAAD, Germany)
- Hungarian Scholarship Board (MOB, Hungary)
- International Max-Planck Research School for Optics and Imaging, Erlangen (IMPRS)
- Alexander von Humboldt Foundation (Germany)
Glaucoma as a neurodegeneration of the optic nerve is one of the most common causes of blindness. Because revitalization of the degenerated nerve fibers of the optic nerve is impossible early detection of the disease is essential. This can be supported by a robust and automated mass-screening. We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. After a glaucoma specific preprocessing, different generic feature types are compressed by an appearance-based dimension reduction technique. Subsequently, a probabilistic two-stage classification scheme combines these features types to extract the novel Glaucoma Risk Index (GRI) that shows a reasonable glaucoma detection performance. On a sample set of 575 fundus images a classification accuracy of 80% has been achieved in a 5-fold cross-validation setup. The GRI gains a competitive area under ROC (AUC) of 88% compared to the established topography-based glaucoma probability score of scanning laser tomography with AUC of 87%. The proposed color fundus image-based GRI achieves a competitive and reliable detection performance on a low-priced modality by the statistical analysis of entire images of the optic nerve head. (C) 2009 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据