MR-PET Head Motion Correction Based on Co-registration of Multicontrast MR Images

Overview

Journal Hum Brain Mapp

Publisher Wiley

Specialty Neurology

Date 2019 Jan 4

PMID 30604898

Citations 7

Authors

Zhaolin Chen

Francesco Sforazzini

Jakub Baran

Thomas Close

Nadim Jon Shah

Gary F Egan

Affiliations

Soon will be listed here.

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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