应用于造影图像的血管中心线全自动提取方法  

Automatic Centerline Extraction Method for X-Ray Angiographic Image

作　　者：肖若秀[1] 杨健[1] 刘越[1] 王涌天[1] 

机构地区：[1]北京理工大学光电学院光电成像技术与系统教育部重点实验室,北京100081

出　　处：《计算机辅助设计与图形学学报》2013年第3期363-371,共9页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家"九七三"重点基础研究发展计划项目(2010CB732505);国家自然科学基金青年基金(60902103);教育部新世纪优秀人才支持计划(NCET-10-0049);北京市优秀人才计划(2010D009011000004)

摘　　要：针对传统血管中心线提取方法计算量大、需大量人工介入操作的问题,提出一种全自动的血管中心线跟踪提取方法.首先根据血管尺度设计不同的Frobenius范数对血管进行自适应增强,并基于血管灰度分布构造多尺度微分算子以建立判别函数,从而获得种子点的初始位置和跟踪方向;然后在初始方向局部弧长范围内优化检测新的脊点与跟踪方向,以确保在有较大误差干扰的情况下依然能够获得正确的脊点位置;最后利用血管拓扑结构特征检测方法剔除伪血管中心线.实验结果证明,该方法无需人工介入即可准确地在冠脉造影图像中提取出血管中心线、方向矢量等信息,可被用于临床心血管疾病的计算机辅助诊疗过程.Current centerline detection methods for vascular trees usually require a large mount of human interactions, which introduces considerable amounts of computation and may lead to large errors. This paper presents a fully automatic vascular centerline extraction method for X-ray angiographic images. First, an adaptive vascular enhancement algorithm is proposed to enhance different scale vascular branches by the Frobenius norm of Hessian matrix. Second, a discriminant function defined on the derivative distribution of the image is utilized to estimate the initial positions and direction vectors of seed points. Then, new ridge points and direction vectors from the initial point are optimized by iteratively calculating the local arc lengths. Third, fake tiny vessels are removed by predefining the number of connecting components. Experiments show that vascular centerline can be extracted automatically and accurately from the X-ray angiographic images. As the developed method is fast and doesn＇t require any human intervention, it can be applied to the clinical application for the diagnosis and treatment of cardiovascular diseases.

关 键 词：血管 多尺度增强 中心线提取 冠脉造影 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]