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On-line 3D motion estimation using low resolution MRI

hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorGLITZNER, Markus
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorDENIS DE SENNEVILLE, Baudouin
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorLAGENDIJK, Jan
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorRAAYMAKERS, Bas
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorCRIJNS, Sjoerd
dc.date.accessioned2024-04-04T03:09:05Z
dc.date.available2024-04-04T03:09:05Z
dc.date.issued2015-09-01
dc.identifier.issn0031-9155
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193581
dc.description.abstractEnImage processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging ( MRI ) guided radiotherapy, intrafraction anatomy snapshots become technically feasible.magnetic resonance ( MR ) imaging provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MR imaging needs to be accelerated without degrading the quality of information.In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, an exemplary 4D dataset of the abdomen is downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version are then evaluated.Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with (2.5mm) 3 voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. (5mm) 3 . In a therapy guidance scenario MRI , imaging speed would accordingly increase approximately fourfold, with acceptable loss of estimated motion quality.
dc.language.isoen
dc.publisherIOP Publishing
dc.title.enOn-line 3D motion estimation using low resolution MRI
dc.typeArticle de revue
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
bordeaux.journalPhysics in Medicine and Biology
bordeaux.page?
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01181385
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01181385v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Physics%20in%20Medicine%20and%20Biology&rft.date=2015-09-01&rft.spage=?&rft.epage=?&rft.eissn=0031-9155&rft.issn=0031-9155&rft.au=GLITZNER,%20Markus&DENIS%20DE%20SENNEVILLE,%20Baudouin&LAGENDIJK,%20Jan&RAAYMAKERS,%20Bas&CRIJNS,%20Sjoerd&rft.genre=article


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