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PET respiratory motion correction: quo vadis?

dc.rights.licenseopenen_US
hal.structure.identifierInstitut de Neurosciences cognitives et intégratives d'Aquitaine [INCIA]
dc.contributor.authorLAMARE, Frederic
ORCID: 0000-0003-1289-7655
dc.contributor.authorBOUSSE, A.
dc.contributor.authorTHIELEMANS, K.
dc.contributor.authorLIU, C.
dc.contributor.authorMERLIN, T.
dc.contributor.authorFAYAD, H.
dc.contributor.authorVISVIKIS, D.
dc.date.accessioned2023-05-05T09:30:05Z
dc.date.available2023-05-05T09:30:05Z
dc.date.issued2022-02-01
dc.identifier.issn1361-6560en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/173257
dc.description.abstractEnPositron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.
dc.language.isoENen_US
dc.subject.enAlgorithms
dc.subject.enArtifacts
dc.subject.enHumans
dc.subject.enImage Processing
dc.subject.enComputer-Assisted
dc.subject.enMagnetic Resonance Imaging
dc.subject.enMotion
dc.subject.enMovement
dc.subject.enMultimodal Imaging
dc.subject.enPositron Emission Tomography Computed Tomography
dc.subject.enPositron-Emission Tomography
dc.title.enPET respiratory motion correction: quo vadis?
dc.title.alternativePhys Med Biolen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1088/1361-6560/ac43fcen_US
dc.subject.halSciences du Vivant [q-bio]/Neurosciences [q-bio.NC]en_US
dc.identifier.pubmed34915465en_US
bordeaux.journalPhysics in Medicine and Biologyen_US
bordeaux.volume67en_US
bordeaux.hal.laboratoriesInstitut de neurosciences cognitives et intégratives d'Aquitaine (INCIA) - UMR 5287en_US
bordeaux.issue3en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.teamImagerie multimodale translationnelleen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcepubmed
hal.identifierhal-04090024
hal.version1
hal.date.transferred2023-05-05T09:30:10Z
hal.exporttrue
workflow.import.sourcepubmed
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Physics%20in%20Medicine%20and%20Biology&rft.date=2022-02-01&rft.volume=67&rft.issue=3&rft.eissn=1361-6560&rft.issn=1361-6560&rft.au=LAMARE,%20Frederic&BOUSSE,%20A.&THIELEMANS,%20K.&LIU,%20C.&MERLIN,%20T.&rft.genre=article


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