ArticleHuman brain mapping2021
MR-PET head motion correction based on co-registration of multicontrast MR images.
Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 29 citations in OpenAlex.
- Technical Optimization Strategies for Amyloid PET Under Challenging Acquisition Conditions: A Comprehensive Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Enhanced data usability in dynamicEJNMMI physics · 2026Article
- Future prospects for image-derived input function in molecular imaging quantification with the 7 T MR-BrainPET insert.Frontiers in neuroscience · 2025Article
- Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.Magma (New York, N.Y.) · 2024Review
- Deep Learning for Image Enhancement and Correction in Magnetic Resonance Imaging-State-of-the-Art and Challenges.Journal of digital imaging · 2023Review
- Frontostriatothalamic effective connectivity and dopaminergic function in the psychosis continuum.Brain : a journal of neurology · 2023Article
- Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex.Scientific data · 2021Article
- MR-PET head motion correction based on co-registration of multicontrast MR images.Human brain mapping · 2021Article
- Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Review
- Simultaneous BOLD-fMRI and constant infusion FDG-PET data of the resting human brain.Scientific data · 2020Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Head motion is a major source of image artefacts in neuroimaging studies and can lead to degradation of the quantitative accuracy of reconstructed PET images. Simultaneous magnetic resonance-positron emission tomography (MR-PET) makes it possible to estimate head motion information from high-resolution MR images and then correct motion artefacts in PET images. In this article, we introduce a fully automated PET motion correction method, MR-guided MAF, based on the co-registration of multicontrast MR images. The performance of the MR-guided MAF method was evaluated using MR-PET data acquired from a cohort of ten healthy participants who received a slow infusion of fluorodeoxyglucose ([18-F]FDG). Compared with conventional methods, MR-guided PET image reconstruction can reduce head motion introduced artefacts and improve the image sharpness and quantitative accuracy of PET images acquired using simultaneous MR-PET scanners. The fully automated motion estimation method has been implemented as a publicly available web-service.
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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.