Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53211, USA.
Magn Reson Med. 2009 Dec;62(6):1574-84. doi: 10.1002/mrm.22161.
Both parallel MRI and compressed sensing (CS) are emerging techniques to accelerate conventional MRI by reducing the number of acquired data. The combination of parallel MRI and CS for further acceleration is of great interest. In this paper, we propose a novel method to combine sensitivity encoding (SENSE), one of the standard methods for parallel MRI, and compressed sensing for rapid MR imaging (SparseMRI), a recently proposed method for applying CS in MR imaging with Cartesian trajectories. The proposed method, named CS-SENSE, sequentially reconstructs a set of aliased reduced-field-of-view images in each channel using SparseMRI and then reconstructs the final image from the aliased images using Cartesian SENSE. The results from simulations and phantom and in vivo experiments demonstrate that CS-SENSE can achieve a reduction factor higher than those achieved by SparseMRI and SENSE individually and outperform the existing method that combines parallel MRI and CS.
并行磁共振成像和压缩感知（CS）都是通过减少采集数据量来加速传统磁共振成像的新兴技术。将并行 MRI 和 CS 相结合以进一步加速具有很大的研究兴趣。在本文中，我们提出了一种将灵敏度编码（SENSE）与 CS 相结合的新方法，SENSE 是并行 MRI 的标准方法之一，CS 用于快速磁共振成像（稀疏磁共振成像），这是一种在笛卡尔轨迹中应用 CS 的新方法。所提出的方法命名为 CS-SENSE，它在每个通道中使用稀疏磁共振成像依次重建一组混叠的降视场图像，然后使用笛卡尔 SENSE 从混叠图像重建最终图像。仿真、体模和活体实验的结果表明，CS-SENSE 可以实现高于稀疏磁共振成像和 SENSE 单独使用的降采样因子，并优于结合并行 MRI 和 CS 的现有方法。
