Gifu University, Graduate School of Medicine, Department of Intelligent Image Information 1-1 Yanagido, Gifu 501-1194, Japan.
J Biomed Opt. 2011 Sep;16(9):096009. doi: 10.1117/1.3622755.
Early diagnosis of glaucoma, which is the second leading cause of blindness in the world, can halt or slow the progression of the disease. We propose an automated method for analyzing the optic disc and measuring the cup-to-disc ratio (CDR) on stereo retinal fundus images to improve ophthalmologists' diagnostic efficiency and potentially reduce the variation on the CDR measurement. The method was developed using 80 retinal fundus image pairs, including 25 glaucomatous, and 55 nonglaucomatous eyes, obtained at our institution. A disc region was segmented using the active contour method with the brightness and edge information. The segmentation of a cup region was performed using a depth map of the optic disc, which was reconstructed on the basis of the stereo disparity. The CDRs were measured and compared with those determined using the manual segmentation results by an expert ophthalmologist. The method was applied to a new database which consisted of 98 stereo image pairs including 60 and 30 pairs with and without signs of glaucoma, respectively. Using the CDRs, an area under the receiver operating characteristic curve of 0.90 was obtained for classification of the glaucomatous and nonglaucomatous eyes. The result indicates potential usefulness of the automated determination of CDRs for the diagnosis of glaucoma.
早期诊断青光眼,这是世界上第二大致盲原因,可以阻止或减缓疾病的进展。我们提出了一种自动分析视盘和测量杯盘比(CDR)的方法,用于分析立体视网膜眼底图像,以提高眼科医生的诊断效率,并可能减少 CDR 测量的变化。该方法使用了 80 对视网膜眼底图像,包括 25 只青光眼和 55 只非青光眼,这些图像都是在我们机构获得的。通过主动轮廓方法,使用亮度和边缘信息对盘区进行分割。使用基于立体视差的视盘深度图对杯区进行分割。测量 CDR,并与专家眼科医生的手动分割结果进行比较。该方法应用于一个新的数据库,该数据库包括 98 对立体图像,其中分别有 60 对和 30 对有和没有青光眼迹象。使用 CDR,对青光眼和非青光眼眼的分类得到了 0.90 的接收器工作特征曲线下面积。结果表明,自动确定 CDR 对青光眼的诊断具有潜在的用处。