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首页> 外文期刊>Journal of magnetic resonance >Gridding and fast Fourier transformation on non-uniformly sparse sampled multidimensional NMR data
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Gridding and fast Fourier transformation on non-uniformly sparse sampled multidimensional NMR data

机译:非均匀稀疏采样多维NMR数据的网格化和快速傅立叶变换

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摘要

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.
机译:对于多维NMR方法,间接维非均匀稀疏采样可以大大缩短实验的采集时间。但是,无法使用快速傅里叶变换(FFT)直接处理非均匀采样的NMR数据。我们表明,可以使用已在MRI中广泛应用的网格化方法将非均匀采样的NMR数据重构为笛卡尔网格,并随后使用FFT对其进行处理。与以前提出的非均匀傅立叶变换相比,提出的网格化FFT(GFFT)方法可显着提高处理速度,并可加快非均匀稀疏采样方法的应用。

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