Journal Article

FZJ-2020-01113

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png MR-PET head motion correction based on co-registration of multicontrast MR images

Chen, Z. (Corresponding author) ; Sforazzini, F. ; Baran, J. ; Close, T. ; Shah, N. J.FZJ* ; Egan, G. F.

2021
Wiley-Liss New York, NY

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Please use a persistent id in citations: http://hdl.handle.net/2128/28501  doi:10.1002/hbm.24497

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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Contributing Institute(s):

1. Physik der Medizinischen Bildgebung (INM-4)

Research Program(s):

1. 573 - Neuroimaging (POF3-573) (POF3-573)
2. 5253 - Neuroimaging (POF4-525) (POF4-525)

Appears in the scientific report 2021

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Database coverage:
; ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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