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Jiao, J.* ; Searle, G.E.* ; Tziortzi, A.C.* ; Salinas, C.A.* ; Gunn, R.N.* ; Schnabel, J.A.*

Spatial-temporal pharmacokinetic model based registration of 4D brain PET data.

Neuroimage 84, 225-235 (2012)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
In dynamic positron emission tomography (PET), where scan durations often exceed 1 hour, registration of motion-corrupted dynamic PET images is necessary in order to maintain the integrity of the physiological/pharmacological/ biochemical information derived from the tracer kinetic analysis of the scan. A pharmacokinetic model, which is traditionally used to analyse PET data following any registration, was incorporated into the registration process itself in order to allow for a groupwise registration of the temporal time frames. The new method achieved smaller registration errors and improved kinetic parameter estimates on validation data sets as compared with the traditional image based similarity registration approach. When applied to measured clinical data from 10 healthy subjects scanned with [ 11C]-(+)-PHNO (a dopamine D3/D2 receptor tracer), it reduced the intra-class variability on the tracer kinetics, suggesting a successful registration. Our new method which incorporates a generic tracer kinetic model could be applied widely to dynamic PET data as part of an automated tool to remove motion artefacts and increase the integrity and statistical power of these data.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
ISSN (print) / ISBN 1053-8119
e-ISSN 1095-9572
Quellenangaben Band: 84, Heft: , Seiten: 225-235 Artikelnummer: , Supplement: ,
Verlag Elsevier
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute for Machine Learning in Biomed Imaging (IML)