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Nonuniform sampling by quantiles

[Display omitted] •Defining equal areas of a sampling function is the basis for a general, flexible, and intuitive strategy for selecting samples for non-uniform-sampling NMR.•The quantile framework is combined with constrained jittering strategies.•Strategies for improving sampling schedules, such...

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Published in:Journal of magnetic resonance (1997) 2018-03, Vol.288, p.109-121
Main Authors: Craft, D. Levi, Sonstrom, Reilly E., Rovnyak, Virginia G., Rovnyak, David
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container_title Journal of magnetic resonance (1997)
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creator Craft, D. Levi
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description [Display omitted] •Defining equal areas of a sampling function is the basis for a general, flexible, and intuitive strategy for selecting samples for non-uniform-sampling NMR.•The quantile framework is combined with constrained jittering strategies.•Strategies for improving sampling schedules, such as triangular backfilling, were developed and tested.•Quantile scheduling promotes seed independence, and shows improved PSF characteristics and higher spectral quality compared to random weighted scheduling. A flexible strategy for choosing samples nonuniformly from a Nyquist grid using the concept of statistical quantiles is presented for broad classes of NMR experimentation. Quantile-directed scheduling is intuitive and flexible for any weighting function, promotes reproducibility and seed independence, and is generalizable to multiple dimensions. In brief, weighting functions are divided into regions of equal probability, which define the samples to be acquired. Quantile scheduling therefore achieves close adherence to a probability distribution function, thereby minimizing gaps for any given degree of subsampling of the Nyquist grid. A characteristic of quantile scheduling is that one-dimensional, weighted NUS schedules are deterministic, however higher dimensional schedules are similar within a user-specified jittering parameter. To develop unweighted sampling, we investigated the minimum jitter needed to disrupt subharmonic tracts, and show that this criterion can be met in many cases by jittering within 25–50% of the subharmonic gap. For nD-NUS, three supplemental components to choosing samples by quantiles are proposed in this work: (i) forcing the corner samples to ensure sampling to specified maximum values in indirect evolution times, (ii) providing an option to triangular backfill sampling schedules to promote dense/uniform tracts at the beginning of signal evolution periods, and (iii) providing an option to force the edges of nD-NUS schedules to be identical to the 1D quantiles. Quantile-directed scheduling meets the diverse needs of current NUS experimentation, but can also be used for future NUS implementations such as off-grid NUS and more. A computer program implementing these principles (a.k.a. QSched) in 1D- and 2D-NUS is available under the general public license.
doi_str_mv 10.1016/j.jmr.2018.01.014
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subjects Data sampling
Nonuniform sampling
Point spread function
Quantiles
Sensitivity
Sparse sampling
title Nonuniform sampling by quantiles
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