Automatic Measurement of Cup-to-Disc Ratio for Retinal Images
Glaucoma is a chronic eye disease which results in irreversible vision loss,and the optic cup-to-disc ratio(CDR)is an essential clinical indicator in diagnosing glaucoma,which means precise optic disc(OD)and optic cup(OC)segmentation become an important task.In this paper,we propose an automatic CDR measurement method.The method includes three stages: OD localization and ROI extraction,simultaneous segmentation of OD and OC,and CDR calculation.In the first stage,the morphological operation and the sliding window are combined to find the OD location and extract the ROI region.In the second stage,an improved deep neural network,named U-Net+CP+FL,which consists of U-shape convolutional architecture,a novel concatenating path and a multi-label fusion loss function,is adopted to simultaneously segment the OD and OC.Based on the segmentation results,the CDR value can be calculated in the last stage.Experimental results on the retinal images from public databases demonstrate that the proposed method can achieve comparable performance with ophthalmologist and superior performance when compared with other existing methods.Thus,our method can be a suitable tool for automated glaucoma analysis.
Glaucoma diagnosis Cup-to-disc ratio (CDR) OD localization OD&OC segmentation Deep neural network
Xin Zhao Fan Guo Beiji Zou Xiyao Liu Rongchang Zhao
School of Information Science and Engineering,Central South University,Changsha 410083,China;Hunan Province Machine Vision and Intelligence Medical Engineering Technology Research Center,Changsha 410083,China
国际会议
广州
英文
453-465
2018-11-23（万方平台首次上网日期，不代表论文的发表时间）