Evidence map›Paper›PMID 39323101›Full record

ArticleMagnetic resonance in medicine2025

Compressed sensing reconstruction for high-SNR, rapid dissolved

Jemima H Pilgrim-Morris, Guilhem J Collier, Ryan S Munro, Graham Norquay, Neil J Stewart, Jim M Wild

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Deep Learning Reconstruction forMagnetic resonance in medicine · 2026
    Article
  2. Article
  3. 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.

Jemima H Pilgrim-MorrisPOLARIS, Section of Medical Imaging and Technologies, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.ORCID 0009-0000-5343-2446
Guilhem J CollierPOLARIS, Section of Medical Imaging and Technologies, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.ORCID 0000-0002-1874-4775
Ryan S MunroPOLARIS, Section of Medical Imaging and Technologies, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
Graham NorquayPOLARIS, Section of Medical Imaging and Technologies, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.ORCID 0000-0002-4108-9035
Neil J StewartPOLARIS, Section of Medical Imaging and Technologies, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.ORCID 0000-0001-8358-394X
Jim M WildPOLARIS, Section of Medical Imaging and Technologies, Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.

Funding

Engineering and Physical Sciences Research Council EP/X025187/1Medical Research Council MR/M008894/1
6 · The paper itself

Abstract

purposeThree-dimensional hyperpolarized

methods

resultsCS reconstruction enabled acquisition time to be halved, and it reduced background noise. Median RBC SNR increased from 6 (2-18) to 11 (2-100) with CS, and there was strong agreement between CS and gridding mean ratio map values (R

conclusionCS reconstruction of dissolved

Indexed as

COVID-19Magnetic Resonance ImagingSignal-To-Noise RatioXenon IsotopesAdultAgedData CompressionErythrocytesFemaleHealthy VolunteersHumansImage Processing, Computer-AssistedLungMaleMiddle AgedPulmonary Disease, Chronic ObstructiveXenon-129Xenon Isotopescompressed sensingdissolved 129Xegas exchangehyperpolarized 129Xelung MRInatural abundance 129Xe

Identifiers

PMID39323101
PMCPMC11604844

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.