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用于二维和三维 MRI 中基于数据一致性的稳健回顾性运动校正的运动引导线。

Motion guidance lines for robust data consistency-based retrospective motion correction in 2D and 3D MRI.

机构信息

Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.

Siemens Healthcare, Erlangen, Germany.

出版信息

Magn Reson Med. 2023 May;89(5):1777-1790. doi: 10.1002/mrm.29534. Epub 2023 Feb 6.

Abstract

PURPOSE

To develop a robust retrospective motion-correction technique based on repeating k-space guidance lines for improving motion correction in Cartesian 2D and 3D brain MRI.

METHODS

The motion guidance lines are inserted into the standard sequence orderings for 2D turbo spin echo and 3D MPRAGE to inform a data consistency-based motion estimation and reconstruction, which can be guided by a low-resolution scout. The extremely limited number of required guidance lines are repeated during each echo train and discarded in the final image reconstruction. Thus, integration within a standard k-space acquisition ordering ensures the expected image quality/contrast and motion sensitivity of that sequence.

RESULTS

Through simulation and in vivo 2D multislice and 3D motion experiments, we demonstrate that respectively 2 or 4 optimized motion guidance lines per shot enables accurate motion estimation and correction. Clinically acceptable reconstruction times are achieved through fully separable on-the-fly motion optimizations (˜1 s/shot) using standard scanner GPU hardware.

CONCLUSION

The addition of guidance lines to scout accelerated motion estimation facilitates robust retrospective motion correction that can be effectively introduced without perturbing standard clinical protocols and workflows.

摘要

目的

开发一种基于重复 k 空间引导线的稳健的回顾性运动校正技术,以提高笛卡尔 2D 和 3D 脑 MRI 的运动校正性能。

方法

将运动引导线插入到 2D 涡轮自旋回波和 3D MPRAGE 的标准序列顺序中,以基于数据一致性的运动估计和重建来告知,该方法可以通过低分辨率的扫描来引导。在每个回波链中重复使用数量非常有限的引导线,并在最终的图像重建中丢弃。因此,在标准的 k 空间采集顺序内进行集成可以确保该序列的预期图像质量/对比度和运动灵敏度。

结果

通过模拟和体内 2D 多切片和 3D 运动实验,我们证明每个采集的 2 或 4 条优化的运动引导线可以实现准确的运动估计和校正。通过使用标准扫描仪 GPU 硬件进行完全可分离的实时运动优化(˜1 s/采集),可以实现临床可接受的重建时间(˜1 s/采集)。

结论

将引导线添加到扫描中加速运动估计,有助于实现稳健的回顾性运动校正,而不会干扰标准的临床协议和工作流程。

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本文引用的文献

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Scout accelerated motion estimation and reduction (SAMER).Scout 加速运动估计和减少 (SAMER)。
Magn Reson Med. 2022 Jan;87(1):163-178. doi: 10.1002/mrm.28971. Epub 2021 Aug 13.
2
MC -Net: motion correction network for multi-contrast brain MRI.MC-Net:用于多对比度脑 MRI 的运动校正网络。
Magn Reson Med. 2021 Aug;86(2):1077-1092. doi: 10.1002/mrm.28719. Epub 2021 Mar 15.
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Head motion measurement and correction using FID navigators.使用 FID 导航器进行头部运动测量和校正。
Magn Reson Med. 2019 Jan;81(1):258-274. doi: 10.1002/mrm.27381. Epub 2018 Jul 29.

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