摘要
针对分割之后的脑血管体数据场,提出基于球B样条曲线结合树状结构的表示模型.该模型中主要分为3个步骤表示脑血管:首先采用Hessian矩阵结合弹性球的方法获取脑血管的中心线和半径信息,可提高中心线的求取精度并且在中心线的求取过程中即可获得半径;然后对获得的中心线和半径进行树状重构,得到符合血管的形态拓扑结构,便于对脑血管进行遍历;最后对重构之后的每一分支血管采用球B样条曲线的方式来描述,以对脑血管病变区域进行检测,并能针对不同大小的显示窗口采用多尺度方式绘制.实验结果表明,文中模型在脑血管的显示、病灶检测等方面具有极大优势.
According to the cerebrovascular volume data after segmentation, the author proposes a cerebrovascular expression model based on ball B-spline curves and tree structure, which can be described as the following three steps. Firstly, we can get the centerline and radius of cerebral vessels according to a hessian matrix combined with elastic ball model, this improves the accuracy of center extraction and get radius simultaneously during the extraction process. Secondly, we deal with the centerline and radius got in the first step by tree reconstruction, because it accords with the topology of vascular and is easy to traverse. Finally, we describe every branch vessel by ball B-spline curves after reconstruction. This method of depiction can detect the lesion areas precisely and can draw the graph in multi-scale way to adapt to the display windows in different sizes. The experimental results show that this model has a great advantage in vessel display and cerebrovascular lesions detection.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2013年第4期541-549,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(61003134
61170170)
北京市自然科学基金重点项目(4081002)
关键词
血管重构
球B样条曲线
中心线提取
树形结构
vessel reconstruction
ball B-spline curve
centerline extraction
tree structure
