锥束CT系统旋转平移轨迹几何参数标定方法

针对锥束CT系统旋转平移（RT）轨迹中几何参数难以直接测量的问题,在单圆轨迹标定方法的基础上,提出了一种适用于RT轨迹的几何参数标定方法。该方法利用定标体模投影轨迹的椭圆参数与系统几何参数建立关系,解析求解出系统的内部参数。在此基础上,外推得到旋转轴所有的位置参数,并求得符合理想轨迹要求的几何参数。所求参数都可以通过解析的公式得到,能有效避免迭代法陷入局部最优的问题。对存在偏差的系统进行了仿真,并利用该方法进行标定,实验结果表明,该方法能有效抑制由于几何参数误差造成的几何伪影,提高图像质量。     

Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

Linear scan computed tomography (LCT) is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation (TV) minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method (ADM) to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.