Xiong Li, Li Huiqi
School of Information and Electronics, Beijing Institute of Technology, No. 5 Zhongguancun Street, Beijing 100081, China.
School of Information and Electronics, Beijing Institute of Technology, No. 5 Zhongguancun Street, Beijing 100081, China.
Comput Med Imaging Graph. 2016 Jan;47:40-50. doi: 10.1016/j.compmedimag.2015.10.003. Epub 2015 Nov 14.
Automatic optic disc (OD) detection is an essential step for screening of eye diseases. An OD localization method is proposed in this paper, which aims to locate OD robustly in retinal image with pathological changes. There are mainly three steps in this approach: region-of-interest (ROI) detection, candidate pixel detection, and confidence score calculation. The features of vessel direction, intensity, OD edges, and size of bright regions were extracted and employed in the proposed OD locating approach. Compared with the OD locating method based on vessel direction only, the proposed method could handle the following cases better: OD partially appears in retinal image, retinal vessels are not obvious in retinal image, or there are bright lesions in retinal images. Four public databases with total 340 retinal images were tested to evaluate the performance of our method. The proposed method can achieve an accuracy of 100%, 95.8%, 99.2%, 97.8% for DRIVE database, STARE database, DIARETDB0 database, DIARETDB1 database respectively. Comparison studies showed that the proposed approach is especially robust in the retinal images with diseases.
自动视盘（OD）检测是眼部疾病筛查的关键步骤。本文提出了一种OD定位方法，旨在在存在病变的视网膜图像中稳健地定位OD。该方法主要有三个步骤：感兴趣区域（ROI）检测、候选像素检测和置信度得分计算。在所提出的OD定位方法中，提取并利用了血管方向、强度、OD边缘和明亮区域大小等特征。与仅基于血管方向的OD定位方法相比，该方法能更好地处理以下情况：OD部分出现在视网膜图像中、视网膜血管在视网膜图像中不明显或视网膜图像中存在明亮病变。使用四个包含总共340张视网膜图像的公共数据库来评估我们方法的性能。对于DRIVE数据库、STARE数据库、DIARETDB0数据库、DIARETDB1数据库，所提出的方法分别可达到100%、95.8%、99.2%、97.8%的准确率。比较研究表明，所提出的方法在患有疾病的视网膜图像中尤其稳健。
