Huo Donglai, Xu Dan, Liang Zhi-Pei, Wilson David
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Magn Reson Imaging. 2006 Feb;24(2):123-32. doi: 10.1016/j.mri.2005.10.018. Epub 2005 Dec 27.
Parallel magnetic resonance imaging through sensitivity encoding using multiple receiver coils has emerged as an effective tool to reduce imaging time or to improve image SNR. The quality of reconstructed images is limited by the inaccurate estimation of the sensitivity map, noise in the acquired k-space data and the ill-conditioned nature of the coefficient matrix. Tikhonov regularization is a popular method to reduce or eliminate the ill-conditioned nature of the problem. In this approach, selection of the regularization map and the regularization parameter is very important. Perceptual difference model (PDM) is a quantitative image quality evaluation tool that has been successfully applied to varieties of MR applications. High correlation between the human rating and PDM score shows that PDM should be suitable to evaluate image quality in parallel MR imaging. By applying PDM, we compared four methods of selecting the regularization map and four methods of selecting the regularization parameter. We found that a regularization map obtained using generalized series (GS) together with a spatially adaptive regularization parameter gave the best reconstructions. PDM was also used as an objective function for optimizing two important parameters in the spatially adaptive method. We conclude that PDM enables one to do comprehensive experiments and that it is an effective tool for designing and optimizing reconstruction methods in parallel MR imaging.
通过使用多个接收线圈的灵敏度编码进行并行磁共振成像已成为减少成像时间或提高图像信噪比的有效工具。重建图像的质量受到灵敏度图估计不准确、采集的k空间数据中的噪声以及系数矩阵的病态性质的限制。蒂霍诺夫正则化是一种减少或消除问题病态性质的常用方法。在这种方法中，正则化图和正则化参数的选择非常重要。感知差异模型（PDM）是一种定量图像质量评估工具，已成功应用于各种磁共振应用。人类评分与PDM分数之间的高度相关性表明，PDM应该适用于评估并行磁共振成像中的图像质量。通过应用PDM，我们比较了四种选择正则化图的方法和四种选择正则化参数的方法。我们发现，使用广义级数（GS）获得的正则化图与空间自适应正则化参数相结合可得到最佳重建效果。PDM还被用作目标函数，用于优化空间自适应方法中的两个重要参数。我们得出结论，PDM使人们能够进行全面的实验，并且它是设计和优化并行磁共振成像重建方法的有效工具。
