Evidence map›Paper›PMID 26256110›Full record

ArticleMagnetic resonance in chemistry : MRC2015

A new approach to compressed sensing for NMR.

Alan S Stern, Jeffrey C Hoch

Abstract read
In one paragraph

Article in Magnetic resonance in chemistry : MRC, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. [Elimination of Gibbs artifact based on local subpixel shift and interlaced local variation].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2019
    Article
  5. Review
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  7. Article
  8. Article
  9. Article
  10. Subrandom methods for multidimensional nonuniform sampling.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2016
    Article
  11. Article
  12. Convex accelerated maximum entropy reconstruction.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2016
    Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alan S SternRowland Institute at Harvard, 100 Edwin H. Land Blvd., Cambridge, MA, 02142, USA.
Jeffrey C HochUConn Health, Department of Molecular Biology and Biophysics, 263 Farmington Ave., Farmington, CT, 06030-3305, USA.

Funding

TRD3 NMRbox: Bayesian AnalyticsP41GM111135 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI HOCH, JEFFREY C · 2015 to 2024
$14.0M
Maximum Entropy Deconvolution for Resolution & Sensitivity Enhancement in Bio-NMRR21GM104517 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI HOCH, JEFFREY C · 2013 to 2014
$437k
NIGMS NIH HHS GM104517NIGMS NIH HHS P41 GM111135NIGMS NIH HHS R21 GM104517
6 · The paper itself

Abstract

Compressed sensing (CS) has attracted a great deal of recent interest as an approach for spectrum analysis of nonuniformly sampled NMR data. Although theoretical justification for the method is abundant, it suffers from several weaknesses, among them poor convergence of some algorithms, and it remains an open question whether NMR spectra satisfy the sparsity requirements of CS theorems. The versions of CS used in NMR involve minimizing the l1 norm of the spectrum. They bear similarity to maximum entropy (MaxEnt) reconstruction, but critical comparison of the methods can be difficult. Here we describe a formalism that places CS and MaxEnt reconstruction on equal footing, enabling critical comparison of the two methods. We also describe a new algorithm for CS that restricts the computation of the l1 norm to the real channel for complex spectra and ensures causality. Preliminary 1D results demonstrate that this approach ameliorates some artifacts that can occur when using the l1 norm of the complex spectrum.

Indexed as

Signal Processing, Computer-AssistedMagnetic Resonance Spectroscopycompressed sensingnon-Fouriersignal processingspectrum analysis

Identifiers

PMID26256110
PMCPMC5776145

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.