Ning Qiang, Ma Chao, Lam Fan, Liang Zhi-Pei
IEEE Trans Biomed Eng. 2017 May;64(5):1178-1186. doi: 10.1109/TBME.2016.2594583. Epub 2016 Jul 27.
To obtain reliable spectral estimation from magnetic resonance spectroscopic imaging (MRSI) data.
The proposed method takes advantage of prior knowledge: 1) along the spectral dimension in the form of spectral bases, and 2) along the spatial dimensions in the form of spatial regularizations (e.g., smoothness or transform sparsity) and jointly estimates parameters from all the voxels.
Simulation and in vivo studies have been performed to demonstrate the performance of the proposed method. A Cramér-Rao-bound-based analysis is also provided.
Incorporation of both spatial and spectral constraints can significantly improve spectral quantification of MRSI data.
The proposed method is expected to be useful for various quantitative MRSI studies.
从磁共振波谱成像(MRSI)数据中获得可靠的频谱估计。
所提出的方法利用了先验知识:1)以频谱基的形式沿频谱维度,以及2)以空间正则化(例如,平滑度或变换稀疏性)的形式沿空间维度,并从所有体素联合估计参数。
已进行模拟和体内研究以证明所提出方法的性能。还提供了基于克拉美罗界的分析。
纳入空间和频谱约束可显著改善MRSI数据的频谱量化。
所提出的方法有望用于各种定量MRSI研究。