ArticleScientific data2022
Movement-related artefacts (MR-ART) dataset of matched motion-corrupted and clean structural MRI brain scans.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 56 citations in OpenAlex.
- Article
- Dual-branch MRI denoising and motion artifact suppression with uncertainty estimation and segmentation-based evaluation.Medical physics · 2026Article
- A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning.Scientific data · 2026Article
- Brain MRI Dataset Featuring a Full Clinical Protocol With and Without Intentional Motion.Scientific data · 2026Article
- Decipher-MR: a vision-language foundation model for 3D MRI representations.NPJ digital medicine · 2026Article
- Deep learning approach to super-resolution correction of brain MRI motion artifacts for accurate hippocampal volumetry.Scientific reports · 2026Article
- Performance of a GPU- and time-efficient pseudo-3D network for magnetic resonance image super-resolution and motion artifact reduction.Scientific reports · 2026Article
- Factors Contributing to Short-Term Structural Variability in a Longitudinal MRI Dataset.Human brain mapping · 2026Article
- Bias in Structural MRI Correlates of Delay Discounting due to Head Motion.Human brain mapping · 2026Article
- Iterative learning for joint image denoising and motion artifact correction of 3D brain MRI.Medical image analysis · 2026Article
- Estimation of head motion in structural MRI and its impact on cortical morphometry.Frontiers in neuroscience · 2026Article
- Res-MoCoDiff: residual-guided diffusion models for motion artifact correction in brain MRI.Physics in medicine and biology · 2025Article
- Systematic Review and Meta-analysis of AI-driven MRI Motion Artifact Detection and Correction.ArXiv · 2025Article
- Res-MoCoDiff: Residual-guided diffusion models for motion artifact correction in brain MRI.ArXiv · 2025Article
- Brain Age Prediction: Deep Models Need a Hand to Generalize.Human brain mapping · 2025Article
- Analysis of Factors Affecting Quality in Structural Magnetic Resonance Images.Human brain mapping · 2025Article
- Charting structural brain asymmetry across the human lifespan.bioRxiv : the preprint server for biology · 2025Article
- InterpolAI: deep learning-based optical flow interpolation and restoration of biomedical images for improved 3D tissue mapping.Nature methods · 2025Article
- Removing facial features from structural MRI images biases visual quality assessment.PLoS biology · 2025Article
- A foundation model for enhancing magnetic resonance images and downstream segmentation, registration and diagnostic tasks.Nature biomedical engineering · 2025Article
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Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
Abstract
Magnetic Resonance Imaging (MRI) provides a unique opportunity to investigate neural changes in healthy and clinical conditions. Its large inherent susceptibility to motion, however, often confounds the measurement. Approaches assessing, correcting, or preventing motion corruption of MRI measurements are under active development, and such efforts can greatly benefit from carefully controlled datasets. We present a unique dataset of structural brain MRI images collected from 148 healthy adults which includes both motion-free and motion-affected data acquired from the same participants. This matched dataset allows direct evaluation of motion artefacts, their impact on derived data, and testing approaches to correct for them. Our dataset further stands out by containing images with different levels of motion artefacts from the same participants, is enriched with expert scoring characterizing the image quality from a clinical point of view and is also complemented with standard image quality metrics obtained from MRIQC. The goal of the dataset is to raise awareness of the issue and provide a useful resource to assess and improve current motion correction approaches.
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Registered trials
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.