标题： 运动补偿极端MRI：高度加速3D动态采集的多尺度低秩重建（MoCo-MSLR） 显示英文标题

标题： Motion Compensated Extreme MRI: Multi-Scale Low Rank Reconstructions for Highly Accelerated 3D Dynamic Acquisitions (MoCo-MSLR)

摘要： 目的：为了改进Ong等人最近提出的一种方法，该方法称为Extreme MRI，通过使用一种称为MoCo-MSLR的方法将运动补偿纳入这些重建中，以重构高时空分辨率的3D非笛卡尔采集数据。 方法：由于运动场的内存占用以及依赖于初始高时间分辨率、低空间分辨率重建可能导致动态丢失，将运动补偿纳入高时空分辨率重建具有挑战性。 受Ong等人和Huttinga等人的工作启发，我们通过k空间中的损失强制估计低空间分辨率运动场，并使用多尺度低秩成分以内存高效的方式表示这些运动场。 我们将这些运动场插值到所需的的空间分辨率，然后将这些场纳入Extreme MRI。 结果：MoCo-MSLR能够改善大约500毫秒时间分辨率的重建图像质量，并捕捉到Extreme MRI中未看到的整体运动。 此外，MoCo-MSLR能够在接近100毫秒的时间分辨率下解析现实的心脏动力学，而Extreme MRI难以解析这些动力学。 结论：MoCo-MSLR在Extreme MRI上提高了图像质量，并能够解析3D中的呼吸和心脏运动。 显示英文摘要

摘要： Purpose: To improve upon Extreme MRI, a recently proposed method by Ong Et al. for reconstructing high spatiotemporal resolution, 3D non-Cartesian acquisitions by incorporating motion compensation into these reconstructions using an approach termed MoCo-MSLR. Methods: Motion compensation is challenging to incorporate into high spatiotemporal resolution reconstruction due to the memory footprint of the motion fields and the potential to lose dynamics by relying on an initial high temporal resolution, low spatial resolution reconstruction. Motivated by the work of Ong Et al. and Huttinga Et al., we estimate low spatial resolution motion fields through a loss enforced in k-space and represent these motion fields in a memory efficient manner using multi-scale low rank components. We interpolate these motion fields to the desired spatial resolution, and then incorporate these fields into Extreme MRI. Results: MoCo-MSLR was able to improve image quality for reconstructions around 500ms temporal resolution and capture bulk motion not seen in Extreme MRI. Further, MoCo-MSLR was able to resolve realistic cardiac dynamics at near 100ms temporal resolution while Extreme MRI struggled to resolve these dynamics. Conclusion: MoCo-MSLR improved image quality over Extreme MRI and was able to resolve both respiratory and cardiac motion in 3D.