Automatic Vessel Extraction for Sclera-conjunctiva Images Based on Exploratory Tracking
Automatic Vessel Extraction for Sclera-conjunctiva Images Based on Exploratory Tracking
复制标题
基于探索性跟踪的巩膜结膜图像自动血管提取
DOI：
--
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Wang Jinjue
中科院分区：
文献类型：
--
作者：
Wang Jinjue
提出了一种用于中医视眼辨证的巩膜结膜血管提取算法。首先通过最优阈值分割和数学运算分离出巩膜结膜区域。在巩膜-结膜区域的扫描线中搜索初始跟踪点。根据当前血管边缘和轮廓分析更新跟踪向量。结果表明，这种全自动方法可以克服血管曲率和直径不连续的问题。
This paper presents algorithms for vessel extraction in sclera-conjunctiva images, which can be applied in syndrome differentiation by observing eyes (traditional Chinese medicine). Sclera-conjunctiva region is isolated by optimal thresholding segmentation and mathematical operation as a first step. The scan lines in sclera-conjunctiva region are searched for the initial tracking points. Tracking vector is updated according to the current vessel edge and profile analysis. The results indicate that this fully automatic method could overcome the problems of discontinuity in vessel curvature and diameter.