论文标题
运动补偿的极端MRI：高加速3D动态采集（MoCO-MSLR）的多尺度低等级重建
Motion Compensated Extreme MRI: Multi-Scale Low Rank Reconstructions for Highly Accelerated 3D Dynamic Acquisitions (MoCo-MSLR)
论文作者
论文摘要
目的：为了改善极端MRI，Ong等人最近提出的一种方法。为了重建高时空分辨率，通过使用称为MOCO-MSLR的方法将运动补偿纳入这些重建中，将3D非卡提斯采集进行。方法：由于运动场的记忆足迹，运动补偿是具有挑战性的，要纳入高时空分辨率重建，并通过依靠初始高时空分辨率，低空间分辨率重建而失去动力学的潜力。由Ong等人的工作激励。和Huttinga等人，我们通过在K空间中强制执行的损耗来估计低空间分辨率运动场，并使用多尺度的低级组件以记忆有效的方式表示这些运动场。我们将这些运动场插入所需的空间分辨率，然后将这些场纳入极端MRI。结果：Moco-MSLR能够改善500ms时间分辨率的重建的图像质量，并捕获极端MRI中未见的散装运动。此外，Moco-MSLR能够以接近100ms的时间分辨率解决现实的心脏动力学，而极端MRI努力解决这些动力学。结论：Moco-MSLR在极端MRI上提高了图像质量，并能够在3D中解决呼吸和心脏运动。
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.
