Evidence map›Paper›PMID 35313378›Full record

ArticleMagnetic resonance in medicine2022

Correcting inter-scan motion artifacts in quantitative R

Yaël Balbastre, Ali Aghaeifar, Nadège Corbin, Mikael Brudfors, John Ashburner, Martina F Callaghan

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
    Review
  6. Correcting inter-scan motion artifacts in quantitative RMagnetic resonance in medicine · 2022
    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

6 authors.

Yaël BalbastreWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0001-8758-9978
Ali AghaeifarWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
Nadège CorbinWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0003-3296-4544
Mikael BrudforsWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
John AshburnerWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.
Martina F CallaghanWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0003-0374-1659

Funding

Medical Research Council MR/R000050/1Wellcome 203147/Z/16/ZWellcome Trust
6 · The paper itself

Abstract

purposeInter-scan motion is a substantial source of error in THEORY: The proposed methods use coil-combined magnitude images to obtain the relative coil sensitivities. The first method efficiently computes the relative sensitivities via a simple ratio; the second by fitting a more sophisticated generative model.

methods

resultsAt 3T, the proposed methods outperform the baseline method. Inter-scan motion artifacts were also reduced at 7T. However, at 7T reproducibility only converged on that of the no motion condition if position-specific transmit field effects were also incorporated.

conclusionThe proposed methods simplify inter-scan motion correction of

Indexed as

ArtifactsMagnetic Resonance ImagingMotionRadionuclide ImagingReproducibility of Results7Tgenerative modelinginter-scan motionqMRIsensitivity

Identifiers

PMID35313378
PMCPMC9314963

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Registered trials

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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.