弹道误差补偿的通用算法：在径向成像中的应用
A General Algorithm For Compensation Of Trajectory Errors: Application To Radial Imaging
摘要：
目的：当实际k空间轨迹由于梯度缺陷而偏离标称轨迹时，根据测量的k空间数据重建无伪影图像。研究方法：由涡流和梯度延迟引起的轨迹误差在几个快速扫描MR脉冲序列中引入相位不一致，导致图像伪影。该算法提供了一种新的框架来补偿这种相位失真。该算法依赖于多块汉克尔矩阵的构造，其中每个块由具有相同相位失真的k空间段构造。在段之间存在空间平滑相位失真的情况下，已知完整的块汉克尔矩阵是高度低秩的。由于每个k空间段仅采集k空间数据的一部分，因此假设线圈灵敏度是已知的，根据它们的部分并行测量重建相位补偿图像被视为结构化的低秩矩阵优化问题。结果：所提出的配方进行了测试，在几种设置，包括部分傅立叶和黄金角收购径向收购。实验表明，该算法能够成功地消除由轨迹误差引起的伪影，而不需要轨迹或相位校准。重建质量与使用轨迹自动校正图像重建（TrACR）进行径向采集所实现的校正相当。结论：所提出的方法提供了一个通用的框架，从径向轨迹恢复无伪影的图像，而不需要轨迹校准。
英文摘要：
Purpose: To reconstruct artifact-free images from measured k-space data, when the actual k-space trajectory deviates from the nominal trajectory due to gradient imperfections. Methods: Trajectory errors arising from eddy currents and gradient delays introduce phase inconsistencies in several fast scanning MR pulse sequences, resulting in image artifacts. The proposed algorithm provides a novel framework to compensate for this phase distortion. The algorithm relies on the construction of a multi-block Hankel matrix, where each block is constructed from k-space segments with the same phase distortion. In the presence of spatially smooth phase distortions between the segments, the complete block-Hankel matrix is known to be highly low-rank. Since each k-space segment is only acquiring part of the k-space data, the reconstruction of the phase compensated image from their partially parallel measurements is posed as a structured low-rank matrix optimization problem, assuming the coil sensitivities to be known. Results: The proposed formulation is tested on radial acquisitions in several settings including partial Fourier and golden-angle acquisitions. The experiments demonstrate the ability of the algorithm to successfully remove the artifacts arising from the trajectory errors, without the need for trajectory or phase calibration. The quality of the reconstruction was comparable to corrections achieved using the Trajectory Auto-Corrected Image Reconstruction (TrACR) for radial acquisitions. Conclusion: The proposed method provides a general framework for the recovery of artifact-free images from radial trajectories without the need for trajectory calibration.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
