分析视网膜眼底图像以分级糖尿病视网膜病变的严重程度。
Analysis of retinal fundus images for grading of diabetic retinopathy severity.
机构信息
Centre for Intelligent Signal and Imaging Research, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan, Malaysia.
出版信息
Med Biol Eng Comput. 2011 Jun;49(6):693-700. doi: 10.1007/s11517-011-0734-2. Epub 2011 Jan 27.
Diabetic retinopathy (DR) is a sight threatening complication due to diabetes mellitus that affects the retina. In this article, a computerised DR grading system, which digitally analyses retinal fundus image, is used to measure foveal avascular zone. A v-fold cross-validation method is applied to the FINDeRS database to evaluate the performance of the DR system. It is shown that the system achieved sensitivity of >84%, specificity of >97% and accuracy of >95% for all DR stages. At high values of sensitivity (>95%), specificity (>97%) and accuracy (>98%) obtained for No DR and severe NPDR/PDR stages, the computerised DR grading system is suitable for early detection of DR and for effective treatment of severe cases.
糖尿病性视网膜病变（DR）是一种由于糖尿病而影响视网膜的威胁视力的并发症。在本文中，使用了一种计算机化的 DR 分级系统，该系统对眼底图像进行数字化分析，用于测量中心无血管区。采用 v 折叠交叉验证方法对 FINDeRS 数据库进行评估，以评估 DR 系统的性能。结果表明，该系统在所有 DR 阶段的敏感性>84％，特异性>97％和准确性>95％。在高灵敏度（>95％），高特异性（>97％）和高准确性（>98％）的情况下，对于无 DR 和严重 NPDR / PDR 阶段，计算机化的 DR 分级系统适用于 DR 的早期检测和严重病例的有效治疗。
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