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相位循环 bSSFP MRI 中伪影抑制的因子化灵敏度估计。

Factorized sensitivity estimation for artifact suppression in phase-cycled bSSFP MRI.

机构信息

Department of Electrical Engineering, Stanford University, CA, USA.

Intelligent Data Analytics Research Program Department, Aselsan Research Center, Ankara, Turkey.

出版信息

NMR Biomed. 2020 Apr;33(4):e4228. doi: 10.1002/nbm.4228. Epub 2020 Jan 27.

Abstract

OBJECTIVE

Balanced steady-state free precession (bSSFP) imaging suffers from banding artifacts in the presence of magnetic field inhomogeneity. The purpose of this study is to identify an efficient strategy to reconstruct banding-free bSSFP images from multi-coil multi-acquisition datasets.

METHOD

Previous techniques either assume that a naïve coil-combination is performed a priori resulting in suboptimal artifact suppression, or that artifact suppression is performed for each coil separately at the expense of significant computational burden. Here we propose a tailored method that factorizes the estimation of coil and bSSFP sensitivity profiles for improved accuracy and/or speed.

RESULTS

In vivo experiments show that the proposed method outperforms naïve coil-combination and coil-by-coil processing in terms of both reconstruction quality and time.

CONCLUSION

The proposed method enables computationally efficient artifact suppression for phase-cycled bSSFP imaging with modern coil arrays. Rapid imaging applications can efficiently benefit from the improved robustness of bSSFP imaging against field inhomogeneity.

摘要

目的

在存在磁场非均匀性的情况下,平衡稳态自由进动(bSSFP)成像是存在带纹伪影的。本研究的目的是确定一种从多线圈多采集数据集重建无带纹 bSSFP 图像的有效策略。

方法

先前的技术要么假设预先执行了天真的线圈组合,导致伪影抑制效果不佳,要么为每个线圈分别进行伪影抑制,这会导致计算负担显著增加。在这里,我们提出了一种定制的方法,对线圈和 bSSFP 灵敏度分布的估计进行因式分解,以提高准确性和/或速度。

结果

体内实验表明,与天真的线圈组合和逐线圈处理相比,该方法在重建质量和时间方面都具有更好的性能。

结论

该方法为具有现代线圈阵列的相控 bSSFP 成像提供了计算效率高的伪影抑制。快速成像应用可以从 bSSFP 成像对磁场非均匀性的更高鲁棒性中受益。

相似文献

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Accelerated phase-cycled SSFP imaging with compressed sensing.加速相控 SSFP 成像与压缩感知。
IEEE Trans Med Imaging. 2015 Jan;34(1):107-15. doi: 10.1109/TMI.2014.2346814. Epub 2014 Aug 12.

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