摘要
从X线图像中提取特定标志物的几何数据是基于X线图像手术导航系统中的一项关键技术。这些几何数据是X线图像几何变形校正及C形臂相机校准的基础。我们提出一种聚类算法用于特征数据的提取。该算法集成了自适应取阈算法和一种快速准连通分量标记算法的优势,仅需对原始灰度图像进行一次扫描处理即可提取出所需的特征数据。算法执行效率高、鲁棒性好。
Extracting landmark geometric data in C-arm X-ray images is a key technique of camera calibration process in a fluoroseopic-image-based surgical navigation system. The geometric data is the basis of X-ray image distortion correction and C-arm camera calibration. In this paper we present an integrated clustering algorithm for landmark geometric data extraction. This proposed alorithm, with the advantages of an adaptive thresholding method as well as of a fast quasi connected-component labeling method, needs only one past to extract the needed geometric data in a gray scale image. It is of high executive efficiency and good robustness as well.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2008年第5期1039-1043,共5页
Journal of Biomedical Engineering
基金
上海市科学技术委员会科技攻关计划项目资助(20042528(3))
关键词
模式识别
图像处理
自适应取阈
连通分量标记
特征提取
Pattern recognition Image processing Adaptive thresholding Component labeling Feature extraction