为构建冠心病辅助诊断系统，为冠状动脉病变检测提供冠脉结构参数，提出一种利用冠状动脉血管中心线获取血管腔壁的算法。该算法以基于二阶Hessian 矩阵血管滤波改进的最小代价路径算法获得的血管中心线为跟踪路径，根据中心线的轨迹计算中心线上过每一个体素点的冠状动脉横截面，利用光线投射法获得冠脉横截面上离散的血管腔壁位置，并结合分段样条拟合方法得到血管腔壁轮廓，最终采用移动立方体算法将各个血管横截面上的腔壁轮廓重建为三维腔壁模型。该算法所得结果能够清晰反映血管腔壁轮廓，且具有较高的计算速度。

To build the system of computer- aided diagnosis for coronary heart disease and provide some parameters for lesion detection, a new method for coronary artery lumen segmentation based on the coronary artery centerline is proposed, which is the result of the algorithm of improved minimal cost path with second order Hessian vessel filter. The method uses the centerline as the tracking path to get every cross section of the vessel, and then ray casting is used for locating the coronary artery lumen along every ray. The disperse coordinates of the lumen location in every ray can be fitted to an outline of the coronary lumen in every cross section by piecewise spline fitting. As a result of all the outlines of coronary artery lumen in cross section reconstruction, a 3D coronary artery lumen can be built by marching cubes algorithm. The result of the method, which has high computing performance, has nice visualization of vessel lumen and can be the basis of the vessel parameter calculation.