Evidence map›Paper›PMID 41266932›Full record

ArticleMagnetic resonance in medicine2026

Deep Learning Reconstruction for

Rajagopalan Sundaresan, Guilhem J Collier, Neil J Stewart, Sudhanya Chatterjee, Ramesh Venkatesan, Jan Wolber, Jim M Wild

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

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

7 authors.

Rajagopalan SundaresanPOLARIS, Division of Clinical Medicine, School of Medicine & Population Health, Faculty of Health, The University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0009-0003-1176-8373
Guilhem J CollierPOLARIS, Division of Clinical Medicine, School of Medicine & Population Health, Faculty of Health, The University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0000-0002-1874-4775
Neil J StewartPOLARIS, Division of Clinical Medicine, School of Medicine & Population Health, Faculty of Health, The University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0000-0001-8358-394X
Sudhanya ChatterjeeGE HealthCare, Bengaluru, India.
Ramesh VenkatesanGE HealthCare, Bengaluru, India.
Jan WolberPOLARIS, Division of Clinical Medicine, School of Medicine & Population Health, Faculty of Health, The University of Sheffield, Sheffield, UK.
Jim M WildPOLARIS, Division of Clinical Medicine, School of Medicine & Population Health, Faculty of Health, The University of Sheffield, Sheffield, UK.

Funding

EPSRC and MRC Prosperity Partnership EP/X025187/1
6 · The paper itself

Abstract

purpose(i) To assess whether

methodsTwenty three-dimensional compressed sensing (CS) accelerated

resultsDL reconstruction qualitatively improved the sharpness, SNR and image quality of

conclusionDL-based CS, denoising and de-ringing significantly improves SNR and image sharpness in 3D

Indexed as

Deep LearningDiffusion Magnetic Resonance ImagingImage Processing, Computer-AssistedXenonXenon IsotopesAdultAgedAlgorithmsAsthmaFeasibility StudiesFemaleHumansIdiopathic Pulmonary FibrosisImage Interpretation, Computer-AssistedLungMaleXenonXenon-129Xenon Isotopes

Identifiers

PMID41266932
PMCPMC12850583

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.