Sheng Hanwei, Dai Peishan, Liu Zhihang, Zhang-Wen Miaoyun, Zhao Yali, Fan Min
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2015 Oct;32(5):1100-5.
In view of the evaluation of fundus image segmentation, a new evaluation method was proposed to make up insufficiency of the traditional evaluation method which only considers the overlap of pixels and neglects topology structure of the retinal vessel. Mathematical morphology and thinning algorithm were used to obtain the retinal vascular topology structure. Then three features of retinal vessel, including mutual information, correlation coefficient and ratio of nodes, were calculated. The features of the thinned images taken as topology structure of blood vessel were used to evaluate retinal image segmentation. The manually-labeled images and their eroded ones of STARE database were used in the experiment. The result showed that these features, including mutual information, correlation coefficient and ratio of nodes, could be used to evaluate the segmentation quality of retinal vessel on fundus image through topology structure, and the algorithm was simple. The method is of significance to the supplement of traditional segmentation evaluation of retinal vessel on fundus image.
针对眼底图像分割的评估,提出了一种新的评估方法,以弥补传统评估方法的不足,传统评估方法仅考虑像素的重叠,而忽略了视网膜血管的拓扑结构。利用数学形态学和细化算法获取视网膜血管拓扑结构。然后计算视网膜血管的三个特征,包括互信息、相关系数和节点比。将细化后的图像特征作为血管拓扑结构用于评估视网膜图像分割。实验中使用了STARE数据库的手动标注图像及其腐蚀后的图像。结果表明,互信息、相关系数和节点比等特征可通过拓扑结构用于评估眼底图像上视网膜血管的分割质量,且该算法简单。该方法对眼底图像上视网膜血管传统分割评估的补充具有重要意义。