Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data.
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data.
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DOI：
10.1007/s10858-016-0072-7
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发表时间：
2017-06
影响因子：
2.7
通讯作者：
Bax A
中科院分区：
文献类型：
--
作者：
Ying J;Delaglio F;Torchia DA;Bax A
描述了一种用于重建非均匀采样的二维、三维和四维核磁共振数据的新算法SILE的实现，该算法利用了核磁共振谱的已知相位和潜在的时间域信号的指数衰减。该方法相对于所选择的采样协议是非常稳健的，并且在其默认模式下，还将截断的时域信号扩展为适度数量的非采样零点。SILE同样可以用来扩展传统的均匀采样数据，作为线性预测的有效多维替代。该程序作为广泛使用的NMRTube软件套件的插件提供，可用于主流应用程序的默认参数，或用于用户控制迭代过程，以可能进一步提高重建质量并降低对计算资源的需求。对于大数据集，该方法是稳健的，并在稀疏度低至约1%，以及最终全真实光谱大小高达300 GB的情况下进行了演示。全采样、常规处理的光谱和随机选择的NUS子集的比较表明，重建质量在峰位保真度和强度方面接近理论极限。SILE本质上消除了与信号的点扩展函数相关的类似噪声的外观，这些信号的默认值比噪声水平高出五倍，但对核磁共振谱中的实际热噪声的影响很小。因此，微笑重建光谱的出现和解释与傅立叶变换产生的全采样光谱非常相似。
Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.