School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
J Magn Reson Imaging. 2011 Jul;34(1):189-95. doi: 10.1002/jmri.22586. Epub 2011 May 25.
To improve the mapping of myelin water fraction (MWF) despite the presence of measurement noise, and to increase the visibility of fine structures in MWF maps.
An anisotropic diffusion filter (ADF) was effectively combined with a spatially regularized nonnegative least squares algorithm (srNNLS) for robust MWF mapping. Synthetic data simulations were performed to assess the effectiveness of this new method. Experimental measurements of signal decay curves were obtained and MWF maps were estimated using the new method and compared with maps estimated using other methods.
MWF mapping was substantially improved in both simulations and experimental data when ADF was combined with the srNNLS algorithm. MWF variability decreased with the use of the proposed method, which in turn resulted in increased visibility of small focal lesions and structures in the MWF maps.
This study demonstrates that the benefits of ADF and srNNLS algorithms can be effectively combined in a synergic way for robust mapping of MWF in the presence of noise. Substantial improvements to MWF mapping can be made using the proposed method.
提高髓鞘水分数（MWF）的映射质量，即使存在测量噪声，也能提高 MWF 图中细微结构的可见度。
将各向异性扩散滤波器（ADF）与空间正则化非负最小二乘算法（srNNLS）有效结合，用于稳健的 MWF 映射。进行了合成数据模拟，以评估这种新方法的有效性。获得了信号衰减曲线的实验测量值，并使用新方法估计了 MWF 图，并与使用其他方法估计的图进行了比较。
当 ADF 与 srNNLS 算法结合使用时，模拟和实验数据中的 MWF 映射都得到了显著改善。使用所提出的方法降低了 MWF 的可变性，从而提高了 MWF 图中小焦点病变和结构的可见度。
本研究表明，ADF 和 srNNLS 算法的优势可以以协同的方式有效地结合起来，用于存在噪声时的稳健 MWF 映射。使用所提出的方法可以显著改善 MWF 映射。
