Sandgren Niclas, Stoica Petre, Frigo Frederick J, Selén Yngve
Systems and Control Division, Department of Information Technology, Uppsala University, P.O. Box 337, SE-751 05 Uppsala, Sweden.
J Magn Reson. 2005 Jul;175(1):79-91. doi: 10.1016/j.jmr.2005.03.019.
The use of phased-array receive coils is a well-known technique to improve the image quality in magnetic resonance imaging studies of, e.g., the human brain. It is common to incorporate proton (1H) magnetic resonance spectroscopy (MRS) experiments in these studies to quantify key metabolites in a region of interest. Detecting metabolites in vivo is often difficult, requiring extensive scans to achieve signal-to-noise ratios (SNR) that provide suitable diagnostic results. Combining the MR absorption spectra obtained from several receive coils is one possible approach to increase the SNR. Previous literature does not give a clear overview of the wide range of possible approaches that can be used to combine MRS data from multiple detector coils. In this paper, we consider the multicoil MRS approach and introduce several signal processing tools to address the problem from different nonparametric, semiparametric, and parametric perspectives, depending on the amount of available prior knowledge about the data. We present a numerical study of these tools using both simulated 1H MRS data and experimental MRS data acquired from a 3T MR scanner.
使用相控阵接收线圈是一种众所周知的技术，可用于提高例如人脑磁共振成像研究中的图像质量。在这些研究中纳入质子（1H）磁共振波谱（MRS）实验以量化感兴趣区域中的关键代谢物是很常见的。在体内检测代谢物通常很困难，需要进行大量扫描以获得能提供合适诊断结果的信噪比（SNR）。将从多个接收线圈获得的磁共振吸收光谱进行组合是提高SNR的一种可能方法。先前的文献并未对可用于组合来自多个检测线圈的MRS数据的各种可能方法给出清晰概述。在本文中，我们考虑多线圈MRS方法，并根据关于数据的可用先验知识的量，从不同的非参数、半参数和参数角度引入几种信号处理工具来解决该问题。我们使用模拟的1H MRS数据和从3T磁共振扫描仪获取的实验MRS数据对这些工具进行了数值研究。
