一种结合并行成像和压缩感知的快速磁共振成像新方法

压缩感知（CS）技术和并行成像技术（主要是SENSE技术、GRAPPA技术等）都能通过减少k空间数据的采集量来加快磁共振成像速度，目前已有一些将两种方法相结合进一步加速磁共振成像速度的方法（例如CS-GRAPPA）.本文针对数据采集和重建这两方面对现有CS-GRAPPA方法进行了改进，采集方式上采用了局部等间隔采集模板以满足GRAPPA重建的要求，并对采集模板进行随机放置以满足CS重建的要求；数据重建时，根据自动校正数据估算GRAPPA算法中欠采行的重建误差，并利用误差的大小确定在CS算法中保真的程度.不同磁共振图像重建实验的结果表明：与现有方法相比，本文方法能够更好地保留原有图像细节并有效减少伪影.

A New Combination Scheme of GRAPPA and Compressed Sensing for Accelerated Magnetic Resonance Imaging

Both compressed sensing (CS) and parallel imaging (PI) can be used to accelerate magnetic resonance imaging (MRI) by under-sampling the k space data.Several methods combining CS and PI have been proposed to further improve the scanning speed.In this paper,we proposed a new approach to combine CS and PI.We used GRAPPA (Generalized Autocalibrating Partially Parallel Acquisitions) algorithm to reconstruct local under-sampled k space data,and CS to reconstruct the whole k space data for each coil.In the CS reconstruction step,we constrained that the reconstructed k space data should be assimilated to both the sampled k space data and the reconstructed k space data by GRAPPA.In addition,we designed a new sampling strategy to improve the quality of image reconstruction.In vivo imaging results demonstrated that the proposed approach could effectively remove artifacts and improve the image quality.