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Intra-MRI Head Motion Tracking and Correction: A Quantitative In Vivo Evaluation Framework
Zakaria Zariry1,2, Franck Lamberton3,4, Robert Frost5,6
1CNRS, Institute of Cognitive Sciences Marc Jeannerod, Bron, France.
NMR in Biomedicine
|August 4, 2026
Summary
A new framework rigorously evaluates head motion correction in MRI. The markerless optical system (MOS) showed better image quality than fat-signal navigator (FatNav), though FatNav improved with neck masking.
Area of Science:
- Medical Imaging
- Neuroimaging
- Biomedical Engineering
Background:
- Head motion is a significant challenge in MRI, limiting image quality and clinical utility.
- Existing motion mitigation strategies lack rigorous in vivo evaluation, hindering optimization and adoption.
- Accurate assessment of tracking accuracy and precision is crucial for developing effective motion correction techniques.
Purpose of the Study:
- To introduce a novel in vivo framework for evaluating MRI head motion mitigation strategies.
- To compare the performance of a markerless optical system (MOS) and a fat-signal navigator (FatNav) using this framework.
- To assess intra-MRI tracking accuracy and precision of these systems against a reference standard.
Main Methods:
- Developed a framework combining visual guidance for reproducible motion and reference standard displacement estimation.
- Six participants underwent 3T T1-weighted brain MRI with visually guided head rotations (2° and 4°) using MOS feedback.
- Compared MOS and FatNav motion estimates against rigid registration of T1-weighted images; assessed image quality using SSIM, PSNR, and focus measures.
Main Results:
- FatNav accuracy was inferior for translations and larger rotations but comparable to MOS for subtle rotations.
- MOS demonstrated superior precision for certain rotations, while FatNav was more precise for subtle pitch.
- MOS-based correction resulted in significantly better T1-weighted image fidelity (higher SSIM, PSNR, focus).
- The framework detected an uncaptured improvement in FatNav performance with neck masking.
Conclusions:
- The proposed framework offers a detailed characterization of in vivo performance differences between motion correction techniques.
- While MOS showed superior overall image quality restoration, the framework revealed nuanced performance variations.
- This evaluation method can guide the optimization and clinical adoption of MRI head motion mitigation strategies.
