| Literature DB >> 30604898 |
Zhaolin Chen1,2, Francesco Sforazzini1, Jakub Baran1,3, Thomas Close1,4, Nadim Jon Shah1,5, Gary F Egan1,6,7.
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.Entities:
Keywords: MR image registration; MR-guided MAF; MR-guided motion correction; PET motion artefacts; PET motion correction; PET/MR; multiple acquisition frame (MAF); simultaneous MR-PET
Mesh:
Year: 2019 PMID: 30604898 PMCID: PMC8357006 DOI: 10.1002/hbm.24497
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038