Improved model-based magnetic resonance spectroscopic imaging
Improved model-based magnetic resonance spectroscopic imaging
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DOI：
10.1109/tmi.2007.898583
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发表时间：
2007-10-01
影响因子：
10.6
通讯作者：
Liang, Zhi-Pei
中科院分区：
文献类型：
--
作者：
Jacob, Mathews;Zhu, Xiaoping;Liang, Zhi-Pei
基于模型的技术有可能在不牺牲信噪比的情况下减少磁共振光谱成像中的伪影并提高分辨率。然而，目前的方法存在一些缺陷，限制了它们在实际应用中的性能。具体地说，经典方案使用的图像模型灵活性较低，导致模型不匹配，从而导致伪影。此外，当前方法的性能受到解剖学参考和光谱成像数据之间的磁场不均匀和空间失配的负面影响。在本文中，我们提出了有效的解决方案来克服这些问题。我们引入了一种更灵活的图像模型，该模型将信号表示为隔区和局部基函数的线性组合。前者表示间隔内的信号变化，而后者捕获由损伤或分割错误引起的局部扰动。由于组合集具有冗余性，因此我们采用稀疏惩罚优化方法进行重构。为了补偿由场不均匀引起的伪影，我们使用交替扫描来估计场图，并将其用于重建。我们将空间失配模拟为仿射变换，其参数由光谱数据估计。
Model-based techniques have the potential to reduce the artifacts and improve resolution in magnetic resonance spectroscopic imaging, without sacrificing the signal-to-noise ratio. However, the current approaches have a few drawbacks that limit their performance in practical applications. Specifically, the classical schemes use less flexible image models that lead to model misfit, thus resulting in artifacts. Moreover, the performance of the current approaches is negatively affected by the magnetic field inhomogeneity and spatial mismatch between the anatomical references and spectroscopic imaging data. In this paper, we propose efficient solutions to overcome these problems. We introduce a more flexible image model that represents the signal as a linear combination of compartmental and local basis functions. The former set represents the signal variations within the compartments, while the latter captures the local perturbations resulting from lesions or segmentation errors. Since the combined set is redundant, we obtain the reconstructions using sparsity penalized optimization. To compensate for the artifacts resulting from field inhomogeneity, we estimate the field map using alternate scans and use it in the reconstruction. We model the spatial mismatch as an affine transformation, whose parameters are estimated from the spectroscopy data.