Department of Electrical Engineering, Stanford University, CA, USA.
Intelligent Data Analytics Research Program Department, Aselsan Research Center, Ankara, Turkey.
NMR Biomed. 2020 Apr;33(4):e4228. doi: 10.1002/nbm.4228. Epub 2020 Jan 27.
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.
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.
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.
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.
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。
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。
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。
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。