Evidence map›Paper›PMID 42026101›Full record

ArticleScientific data2026

Brain MRI Dataset Featuring a Full Clinical Protocol With and Without Intentional Motion.

Kathrine Skak Madsen, Tim Ruschke, Hannah Eichhorn, Puk Rising, Melanie Ganz

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Kathrine Skak MadsenDanish Research Centre for Magnetic Resonance, Department of Radiology and Nuclear Medicine, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark.
Tim RuschkeNeurobiology Research Unit, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Hannah EichhornInstitute of Machine Learning in Biomedical Imaging, Helmholtz Munich, Neuherberg, Germany.
Puk RisingNeurobiology Research Unit, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Melanie GanzNeurobiology Research Unit, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark. melanie.ganz@nru.dk.ORCID http://orcid.org/0000-0002-9120-8098

Funding

Elsass Fonden (Elsass Foundation) 18-3-0147
6 · The paper itself

Abstract

Motion-induced artefacts in MRI are a common occurrence but can obscure pathologies or be falsely identified as pathological. Reacquiring motion-corrupted scans is expensive, and thus retrospective and prospective motion correction methods have been introduced. Although motion correction shows promise, there is a lack of exhaustive testing on its efficacy with respect to full clinical cerebral MRI protocols. Here we present a dataset (n = 22) to facilitate future research, which includes data with and without intentional motion, and with and without prospective motion correction, across six MRI sequences included in a full clinical cerebral MRI protocol. Motion was captured by an external tracking device, and the dataset includes the motion data as derived motion transforms. For standardization, all image data are fully BIDS-compliant. Raw k-space data are available as well. As the dataset pairs motion-free data with motion-corrupted data, it can be used to develop or test different motion-correction or k-space reconstruction methods.

Indexed as

BrainMagnetic Resonance ImagingMotionArtifactsHumansImage Processing, Computer-Assisted

Identifiers

PMID42026101
PMCPMC13315939

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.