Evidence map›Paper›PMID 30604144›Full record

ArticleMagma (New York, N.Y.)2019

Improved compressed sensing reconstruction for

Thomas Kampf, Volker J F Sturm, Thomas C Basse-Lüsebrink, André Fischer, Lukas R Buschle, Felix T Kurz, Heinz-Peter Schlemmer, Christian H Ziener, Sabine Heiland, Martin Bendszus and 3 more

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In one paragraph

Article in Magma (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
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

13 authors.

Thomas KampfDepartment of Neuroradiology, University Hospital Würzburg, 97080, Würzburg, Germany. Kampf_T@ukw.de.ORCID 0000-0002-9905-0184
Volker J F SturmExperimental Neuroradiology, University Hospital Heidelberg, 69120, Heidelberg, Germany.
Thomas C Basse-LüsebrinkExperimental Physics V, University of Würzburg, 97074, Würzburg, Germany.
André FischerExperimental Physics V, University of Würzburg, 97074, Würzburg, Germany.
Lukas R BuschleGerman Cancer Research Center, 69120, Heidelberg, Germany.
Felix T KurzExperimental Neuroradiology, University Hospital Heidelberg, 69120, Heidelberg, Germany.
Heinz-Peter SchlemmerGerman Cancer Research Center, 69120, Heidelberg, Germany.
Christian H ZienerGerman Cancer Research Center, 69120, Heidelberg, Germany.
Sabine HeilandExperimental Neuroradiology, University Hospital Heidelberg, 69120, Heidelberg, Germany.
Martin BendszusDepartment of Neuroradiology, University Hospital Heidelberg, 69120, Heidelberg, Germany.
Mirko PhamDepartment of Neuroradiology, University Hospital Würzburg, 97080, Würzburg, Germany.
Guido StollDepartment of Neurology, University Hospital Würzburg, 97080, Würzburg, Germany.
Peter M JakobExperimental Physics V, University of Würzburg, 97074, Würzburg, Germany.

Funding

German Research Council KU3555/1-1German Research Council ZI1295/2-1
6 · The paper itself

Abstract

objectiveIn magnetic resonance imaging (MRI), compressed sensing (CS) enables the reconstruction of undersampled sparse data sets. Thus, partial acquisition of the underlying k-space data is sufficient, which significantly reduces measurement time. While MATERIALS AND

methodsTwo resampling strategies in combination with CS reconstructions are presented. Numerical simulations are performed for low-SNR spatially sparse data obtained from

resultsAn improvement in overall image quality compared to conventional CS reconstructions was observed for both strategies. Specifically spike artifacts in the background were suppressed, while the changes in signal pixels remained small. DISCUSSION: The proposed methods improve the quality of CS reconstructions. Furthermore, because resampling is applied during post-processing, no additional measurement time is required. This allows easy incorporation into existing protocols and application to already measured data.

Indexed as

Fluorine-19 Magnetic Resonance ImagingAlgorithmsAnimalsArtifactsComputational BiologyComputer SimulationData CompressionFluorineHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedImaging, Three-DimensionalMiceModels, TheoreticalNormal DistributionPhantoms, ImagingFluorine19FArtifactCompressed sensingCSIMRIMRSISparse

Identifiers

PMID30604144

What OpenQuestion holds

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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.