Department of Information Engineering, University of Padova, 35131 Padova, Italy.
IEEE Trans Biomed Eng. 2011 Mar;58(3):818-21. doi: 10.1109/TBME.2010.2085001. Epub 2010 Oct 14.
A novel system for the vascular tree identification and the quantitative estimation of arteriolar venular ratio clinical index in retinal fundus images is presented. The system is composed of a module for automatic vascular tracking, an interactive editing interface to correct errors and set the required parameters of analysis, and a module for the computation of clinical indexes. The system was organized as a client-server structure to allow clinicians and researchers from all over the world to work remotely. The system was evaluated by three graders analyzing 30 fundus images. The evaluation of the Pearson's correlation coefficient and p-value of a paired t-test for each pair of graders demonstrates the high reproducibility of the measures provided by the system.
本文提出了一种新的视网膜眼底图像血管树识别和动静脉比临床指标定量估计系统。该系统由一个自动血管跟踪模块、一个用于纠正错误和设置分析所需参数的交互编辑界面以及一个用于计算临床指标的模块组成。该系统采用客户端-服务器结构,允许来自世界各地的临床医生和研究人员远程工作。该系统通过三名分级员分析 30 张眼底图像进行了评估。对每对分级员的 Pearson 相关系数和配对 t 检验的 p 值的评估表明,系统提供的测量具有很高的可重复性。