Computed tomography (CT) relies on precise patient immobilization during image acquisition. Nevertheless, motion artifacts in the reconstructed images can persist. Motion compensation methods aim to correct such artifacts post-acquisition, often incorporating temporal smoothness constraints on the estimated motion patterns. This study analyzes the influence of a spline-based motion model within an existing rigid motion compensation algorithm for cone-beam CT on the recoverable motion frequencies. Results demonstrate that the choice of motion model crucially influences recoverable frequencies. The optimization-based motion compensation algorithm is able to accurately fit the spline nodes for frequencies almost up to the node-dependent theoretical limit according to the Nyquist-Shannon theorem. Notably, a higher node count does not compromise reconstruction performance for slow motion patterns, but can extend the range of recoverable high frequencies for the investigated algorithm. Eventually, the optimal motion model is dependent on the imaged anatomy, clinical use case, and scanning protocol and should be tailored carefully to the expected motion frequency spectrum to ensure accurate motion compensation.

通过分析在锥束CT上的一个刚性运动补偿算法中，基于样条的运动模型对可恢复频率的影响，研究发现：选择合适的运动模型对恢复频率至关重要，优化的运动补偿算法能够准确拟合样条节点，但对于慢运动模式，节点数的增加不会损害重建性能，反而可以扩大可恢复的高频范围。最终，最佳的运动模型应根据图像解剖、临床用途和扫描协议进行精心调整，以确保准确的运动补偿。

关于平滑限制对计算机断层摄影运动补偿的影响