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糖尿病视网膜病变图像的自动化分析:原理、最新进展和新兴趋势。

Automated analysis of diabetic retinopathy images: principles, recent developments, and emerging trends.

机构信息

School of Computing, Informatics & Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA.

出版信息

Curr Diab Rep. 2013 Aug;13(4):453-9. doi: 10.1007/s11892-013-0393-9.

Abstract

Diabetic retinopathy (DR) is a vision-threatening complication of diabetes. Timely diagnosis and intervention are essential for treatment that reduces the risk of vision loss. A good color retinal (fundus) photograph can be used as a surrogate for face-to-face evaluation of DR. The use of computers to assist or fully automate DR evaluation from retinal images has been studied for many years. Early work showed promising results for algorithms in detecting and classifying DR pathology. Newer techniques include those that adapt machine learning technology to DR image analysis. Challenges remain, however, that must be overcome before fully automatic DR detection and analysis systems become practical clinical tools.

摘要

糖尿病视网膜病变 (DR) 是糖尿病致盲的严重并发症。及时诊断和干预对降低视力丧失风险的治疗至关重要。良好的彩色眼底 (视网膜) 照片可用作 DR 面对面评估的替代方法。多年来,人们一直在研究使用计算机辅助或全自动从视网膜图像中评估 DR。早期工作表明,用于检测和分类 DR 病理的算法取得了有希望的结果。较新的技术包括将机器学习技术应用于 DR 图像分析的技术。然而,在全自动 DR 检测和分析系统成为实用的临床工具之前,仍然存在必须克服的挑战。

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