使用重加权l(1)最小化的多通道数据改进压缩感知磁共振成像
Improved compressed sensing MRI with multi-channel data using reweighted l(1) minimization.
作者信息
Chang Ching-Hua, Ji Jim
机构信息
Department of Electrical and Computer Engineering, Texas A&M University, TX 77843-3128, USA.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:875-8. doi: 10.1109/IEMBS.2010.5627890.
Compressed sensing (CS) is an emerging technology to speed up magnetic resonance imaging (MRI). Since most clinical MRI scanners are equipped with multi-channel receiver systems, there has been a number of works to integrate CS with multi-channel systems. In this paper, we propose a method that extends the reweighted l(1) minimization to the CS MRI with multi-channel data. The simulated experimental results show that the new method can provide improved reconstruction quality.
压缩感知（CS）是一种用于加速磁共振成像（MRI）的新兴技术。由于大多数临床MRI扫描仪都配备了多通道接收系统，因此已有许多将CS与多通道系统相结合的工作。在本文中，我们提出了一种将重新加权的l(1)最小化扩展到多通道数据的CS MRI的方法。模拟实验结果表明，新方法可以提供更高的重建质量。
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