基于鲁棒估计的并行磁共振成像中部分数据重建算法

摘要

Partial Fourier acquisition and parallel imaging are two effective fast imaging tech-niques. Both techniques permit decreased acquisition times by reducing the amount of phased en-coding needed. The benefits of the combined technique compared with the individual techniques are large reduced imaging time. Unfortunately, during the partial Fourier reconstruction process-ing, restoration of missing uncollected k-space data rely on corrupt Hermitian conjugate symme-try. This leads to minor phase variations and noise introduced, which in turn corrupt in SENSE process. In this paper, a constrained reconstruction algorithm is presented to remove artifact in images. We apply robust Annealing M (AM) Estimator scheme to suppress the corrupt data points and make solutions insensitive to the influence caused by outliers. Experimental results show that proposed method can effectively eliminate aliasing artifacts to enhance quality of recon-struction and imaging speed.%部分傅立叶数据重建和多通道并行成像是两种有效的磁共振快速成像技术,两种技术都是通过减少梯度编码步数来缩短数据获取时间.结合技术相比于单项技术可以更加有效地提高扫描速度.但是,由于在部分数据恢复过程中由于共轭对称性的破坏会产生破坏数据并且带来相位偏移,使得在之后进行的并行重建过程产生误差,造成重建图像产生伪影.文中提出了一种新的约束重建算法去消除重建图像中产生的伪影.算法应用AM鲁棒估计的框架对破坏数据进行数据修正,很好地抑制了异常值对数据集造成的影响.实验结果显示文中算法达到了优质快速成像的目的,更具有实用性.