ArticleIEEE transactions on medical imaging2025
HERON: High-Efficiency Real-Time Motion Quantification and Re-Acquisition for Fetal Diffusion MRI.
Article in IEEE transactions on medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Real-Time Targeted Slice Reacquisition for Motion-Corrupted Fetal Diffusion MRI.Magnetic resonance in medicine · 2026Article
- Harmonization in magnetic resonance imaging: A survey of acquisition, image-level, and feature-level methods.Medical image analysis · 2026Review
- Imaging of Embryonic and Fetal Brain Development Using MRI Microscopy: Achieving High Spatial Resolution.Medical sciences (Basel, Switzerland) · 2026Review
- Potential Benefits of Ultra-High Field MRI for Embryonic and Fetal Brain Investigation: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Scanner-based real-time automated volumetry reporting of the fetus, amniotic fluid, placenta, and umbilical cord for fetal MRI at 0.55T.Magnetic resonance in medicine · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Fetal diffusion MRI (dMRI) provides fascinating and clinically crucial insights into the microstructure of the human brain during development, but is highly sensitive to motion artifacts of fetal movement and maternal breathing, which impact data quality and limit diagnostic accuracy. This study introduces HERON, a robust, real-time, automatic pipeline designed to enhance fetal brain dMRI by performing motion assessment and re-acquisition. HERON leverages AI-driven brain localization, segmentation, and motion assessment on a clinical 0.55T scanner to automatically plan, quality check, and reacquire motion-affected dMRI volumes. Remaining inter-volume motion is corrected during post-processing. Tested in 20 cases, the pipeline effectively improved image quality, reduced intra- and inter-volume motion, and enabled more reliable quantitative analysis even in challenging cases. Excellent agreement with human observers (specificity 97%, sensitivity 92%) was shown and the mean Apparent Diffusion Coefficient and Intravoxel Incoherent Motion dropped in the majority of cases after correction. Improving fetal dMRI through an automatic AI-driven pipeline enables higher diagnostic quality and thus potentially wider use in both research and clinical applications.
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Registered trials
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