Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA.
Magn Reson Med. 2010 Oct;64(4):1135-9. doi: 10.1002/mrm.22481.
Compressed sensing (CS) is a promising method to speed up MRI. Because most clinical MRI scanners are equipped with multichannel receive systems, integrating CS with multichannel systems may not only shorten the scan time but also provide improved image quality. However, significant computation time is required to perform CS reconstruction, whose complexity is scaled by the number of channels. In this article, we propose a reconstruction procedure that uses ubiquitously available multicore central processing unit to accelerate CS reconstruction from multiple channel data. The experimental results show that the reconstruction efficiency benefits significantly from parallelizing the CS reconstructions and pipelining multichannel data into multicore processors. In our experiments, an additional speedup factor of 1.6-2.0 was achieved using the proposed method on a quad-core central processing unit. The proposed method provides a straightforward way to accelerate CS reconstruction with multichannel data for parallel computation.
压缩感知（CS）是一种加速 MRI 的有前途的方法。由于大多数临床 MRI 扫描仪都配备了多通道接收系统，因此将 CS 与多通道系统集成不仅可以缩短扫描时间，还可以提供更高的图像质量。然而，CS 重建需要大量的计算时间，其复杂性与通道数量成正比。在本文中，我们提出了一种重建过程，该过程使用普遍可用的多核中央处理器来加速来自多个通道的数据的 CS 重建。实验结果表明，通过并行化 CS 重建和将多通道数据流水线到多核处理器中，可以显著提高重建效率。在我们的实验中，在四核中央处理器上使用所提出的方法可以实现 1.6-2.0 的额外加速因子。该方法为使用多通道数据进行并行计算加速 CS 重建提供了一种简单的方法。
