ArticleHuman brain mapping2024
Diffusion MRI head motion correction methods are highly accurate but impacted by denoising and sampling scheme.
Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Did you know? State-of-the-art preprocessing diffusion MRI data can improve tractography.Brain structure & function · 2026Review
- An open, fully-processed data resource for studying mood and sleep variability in the developing brain.Aperture neuro · 2026Article
- Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross-Sectional Datasets Across the Lifespan.Human brain mapping · 2025Article
- A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.Human brain mapping · 2024Article
- Diffusion MRI head motion correction methods are highly accurate but impacted by denoising and sampling scheme.Human brain mapping · 2024Article
- Denoising diffusion MRI: Considerations and implications for analysis.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Optimization and validation of the DESIGNER preprocessing pipeline for clinical diffusion MRI in white matter aging.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex.Nature communications · 2023Article
- Establishing the Validity of Compressed Sensing Diffusion Spectrum Imaging.bioRxiv : the preprint server for biology · 2023Article
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Authors and funding
13 authors at 6 institutions in 1 country.
Funding
Abstract
Head motion correction is particularly challenging in diffusion-weighted MRI (dMRI) scans due to the dramatic changes in image contrast at different gradient strengths and directions. Head motion correction is typically performed using a Gaussian Process model implemented in FSL's Eddy. Recently, the 3dSHORE-based SHORELine method was introduced that does not require shell-based acquisitions, but it has not been previously benchmarked. Here we perform a comprehensive evaluation of both methods on realistic simulations of a software fiber phantom that provides known ground-truth head motion. We demonstrate that both methods perform remarkably well, but that performance can be impacted by sampling scheme and the extent of head motion and the denoising strategy applied before head motion correction. Furthermore, we find Eddy benefits from denoising the data first with MP-PCA. In sum, we provide the most extensive known benchmarking of dMRI head motion correction, together with extensive simulation data and a reproducible workflow. PRACTITIONER POINTS: Both Eddy and SHORELine head motion correction methods performed quite well on a large variety of simulated data. Denoising with MP-PCA can improve head motion correction performance when Eddy is used. SHORELine effectively corrects motion in non-shelled diffusion spectrum imaging data.
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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.