MR-PET head motion correction based on co-registration of multicontrast MR images

Zhaolin Chen, Francesco Sforazzini, Jakub Baran, Thomas Close, Nadim Jon Shah, Gary F. Egan

Research output: Contribution to journalArticleResearchpeer-review

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.

Original languageEnglish
Number of pages11
JournalHuman Brain Mapping
DOIs
Publication statusAccepted/In press - 1 Jan 2019

Keywords

  • MR image registration
  • MR-guided MAF
  • MR-guided motion correction
  • multiple acquisition frame (MAF)
  • PET motion artefacts
  • PET motion correction
  • PET/MR
  • simultaneous MR-PET

Cite this

Chen, Zhaolin ; Sforazzini, Francesco ; Baran, Jakub ; Close, Thomas ; Shah, Nadim Jon ; Egan, Gary F. / MR-PET head motion correction based on co-registration of multicontrast MR images. In: Human Brain Mapping. 2019.
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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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MR-PET head motion correction based on co-registration of multicontrast MR images. / Chen, Zhaolin; Sforazzini, Francesco; Baran, Jakub; Close, Thomas; Shah, Nadim Jon; Egan, Gary F.

In: Human Brain Mapping, 01.01.2019.

Research output: Contribution to journalArticleResearchpeer-review

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