State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, The Chinese Academy of Sciences, Wuhan 430071, China.
J Magn Reson. 2010 May;204(1):165-8. doi: 10.1016/j.jmr.2010.02.009. Epub 2010 Feb 20.
For multidimensional NMR method, indirect dimensional non-uniform sparse sampling can dramatically shorten acquisition time of the experiments. However, the non-uniformly sampled NMR data cannot be processed directly using fast Fourier transform (FFT). We show that the non-uniformly sampled NMR data can be reconstructed to Cartesian grid with the gridding method that has been wide applied in MRI, and sequentially be processed using FFT. The proposed gridding-FFT (GFFT) method increases the processing speed sharply compared with the previously proposed non-uniform Fourier Transform, and may speed up application of the non-uniform sparse sampling approaches.
对于多维 NMR 方法，间接维度非均匀稀疏采样可以显著缩短实验的采集时间。然而，非均匀采样的 NMR 数据不能直接使用快速傅里叶变换（FFT）进行处理。我们表明，可以使用已经广泛应用于 MRI 的网格化方法将非均匀采样的 NMR 数据重建到笛卡尔网格上，并使用 FFT 进行顺序处理。与之前提出的非均匀傅里叶变换相比，所提出的网格化-FFT（GFFT）方法大大提高了处理速度，并且可能加速非均匀稀疏采样方法的应用。
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