A subspace approach to high-resolution spectroscopic imaging.
A subspace approach to high-resolution spectroscopic imaging.
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DOI：
10.1002/mrm.25168
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发表时间：
2014-04
影响因子：
3.3
通讯作者：
Liang, Zhi-Pei
中科院分区：
文献类型：
--
作者：
Lam, Fan;Liang, Zhi-Pei
关键词：
使用（k，t）空间的稀疏采样和子空间（或低秩）建模来加速光谱成像，以实现具有良好信噪比（SNR）的高分辨率代谢成像。所提出的方法，称为SPICE（光谱成像通过利用空间光谱相关性），利用了一个独特的属性称为部分分离的光谱信号。这一性质表明，高维光谱信号驻留在一个非常低维的子空间，并使特殊的数据采集和图像重建策略，以获得高分辨率的空间光谱分布具有良好的SNR。更具体地说，提出了一种混合CSI/EPSI脉冲序列的（k，t）-空间的稀疏采样，并提出了一种基于低秩模型的算法，从稀疏数据的子空间估计和图像重建的能力，将先验信息和字段不均匀性校正。SPICE的性能已通过计算机模拟和体模研究进行了评估，得出了非常令人鼓舞的结果。对于代谢物体模上的2D光谱成像实验，实现了10倍的加速，与长CSI实验相比SNR损失最小，与加速EPSI实验相比SNR显著增加。SPICE能够显著加速光谱成像实验，使高分辨率代谢成像成为可能。
To accelerate spectroscopic imaging using sparse sampling of (k, t)-space and subspace (or low-rank) modeling to enable high-resolution metabolic imaging with good signal-to-noise ratio (SNR). The proposed method, called SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation), exploits a unique property known as partial separability of spectroscopic signals. This property indicates that high-dimensional spectroscopic signals reside in a very low-dimensional subspace and enables special data acquisition and image reconstruction strategies to be used to obtain high-resolution spatiospectral distributions with good SNR. More specifically, a hybrid CSI/EPSI pulse sequence is proposed for sparse sampling of (k, t)-space, and a low-rank model-based algorithm is proposed for subspace estimation and image reconstruction from sparse data with the capability to incorporate prior information and field inhomogeneity correction. The performance of SPICE has been evaluated using both computer simulations and phantom studies, which produced very encouraging results. For 2D spectroscopic imaging experiments on a metabolite phantom, a factor of 10 acceleration was achieved with a minimal loss in SNR compared to the long CSI experiments and with a significant gain in SNR compared to the accelerated EPSI experiments. SPICE is able to significantly accelerate spectroscopic imaging experiments, making high-resolution metabolic imaging possible.
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影响因子：
3.3
作者：
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通讯作者：
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影响因子：
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影响因子：
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通讯作者：
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影响因子：
3.3
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通讯作者：
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