采用高频能量的CT几何参数自标定方法

针对锥束CT系统中几何参数失配引起几何伪影的问题，提出了一种采用空域高频能量的几何伪影自校正算法。该算法以重建图像的空域高频能量为目标函数建立优化模型，通过单纯形法迭代求解使空域高频能量最大的几何参数最优解。利用投影图像的特性提取部分参数作为输入初值，减小算法搜索范围。并采用图形处理器（Graphic Processing Unit，GPU）对自校正过程中的图像重建并行加速，减少重建时间，提高校正速度。实验结果表明:该算法具有较高的求解精度，最大相对误差不超过5%，对重建图像中的几何伪影有较好的校正效果。同时，在不影响精度的情况下减少了迭代次数，算法执行效率提高了18.8%。

Automatic geometric calibration method based on high frequency energy for CT

A self-calibration method based on spatial high frequency energy was proposed in view of the geometric artifacts caused by misaligned geometry in cone-beam CT. An optimization model was constructed based on spatial high frequency energy of the reconstructed image. Part of the parameters were directly extracted from the projection image to diminish the search scope, and the optimal solution of geometry parameters was achieved by NM-simplex method that makes the spatial high frequency energy of CT image maximize. To improve the speed of the algorithm, GPU was used to accelerate the process of image reconstruction to reduce the reconstruction time. Without reprocessing the reconstructed image, the proposed method has less computing complexity compared with the existing ones. The experiment results show that the presented method has significant effect in geometric artifact calibration of the reconstructed images with high accuracy and the maximum relative error is less than 5%. It can notably reduce iterations without precision reduction, and algorithm execution efficiency has been raised 18.8%.