DC FieldValueLanguage
dc.contributor.authorGdaniec, Nadine-
dc.contributor.authorSchlüter, Matthias-
dc.contributor.authorMöddel, Martin-
dc.contributor.authorKaul, Michael-
dc.contributor.authorKrishnan, Kannan M.-
dc.contributor.authorSchlaefer, Alexander-
dc.contributor.authorKnopp, Tobias-
dc.date.accessioned2019-09-26T09:43:41Z-
dc.date.available2019-09-26T09:43:41Z-
dc.date.issued2017-02-09-
dc.identifier.citationIEEE Transactions on Medical Imaging 7 (36): 1511-1521 (2017)de_DE
dc.identifier.issn0278-0062de_DE
dc.identifier.urihttp://hdl.handle.net/11420/3442-
dc.description.abstractThe temporal resolution of the tomographic imaging method magnetic particle imaging (MPI) is remarkably high. The spatial resolution is degraded for measured voltage signal with low signal-to-noise ratio, because the regularization in the image reconstruction step needs to be increased for system-matrix approaches and for deconvolution steps in x-space approaches. To improve the signal-to-noise ratio, blockwise averaging of the signal over time can be advantageous. However, since block-wise averaging decreases the temporal resolution, it prevents resolving the motion. In this paper, a framework for averaging motion-corrupted MPI raw data is proposed. The motion is considered to be periodic as it is the case for respiration and/or the heartbeat. The same state of motion is thus reached repeatedly in a time series exceeding the repetition time of the motion and can be used for averaging. As the motion process and the acquisition process are, in general, not synchronized, averaging of the captured MPI raw data corresponding to the same state of motion requires to shift the starting point of the individual frames. For high-frequency motion, a higher frame rate is potentially required. To address this issue, a binning method for using only parts of complete frames from a motion cycle is proposed that further reduces the motion artifacts in the final images. The frequency of motion is derived directly from the MPI raw data signal without the need to capture an additional navigator signal. Using a motion phantom, it is shown that the proposed method is capable of averaging experimental data with reduced motion artifacts. The methods are further validated on in-vivo data from mouse experiments to compensate the heartbeat.en
dc.description.sponsorshipSupported in part by the German Research Foundation through DFGunder Grant AD 125/5-1 and Grant KN 1108/2-1 and in part by NIH under Grant NIH 2R42EB013520-02A1 and Grant NIH 1R24-MH109085.de_DE
dc.language.isoende_DE
dc.publisherIEEEde_DE
dc.relation.ispartofIEEE transactions on medical imagingde_DE
dc.subjectBiomedical imagingde_DE
dc.subjectMotion artifactsde_DE
dc.subjectMotion compensationde_DE
dc.subjectMotion detectionde_DE
dc.subject.ddc600: Technikde_DE
dc.subject.ddc610: Medizinde_DE
dc.titleDetection and compensation of periodic motion in magnetic particle imagingde_DE
dc.typeArticlede_DE
dc.type.diniarticle-
dc.subject.ddccode600-
dc.subject.ddccode610-
dcterms.DCMITypeText-
tuhh.abstract.englishThe temporal resolution of the tomographic imaging method magnetic particle imaging (MPI) is remarkably high. The spatial resolution is degraded for measured voltage signal with low signal-to-noise ratio, because the regularization in the image reconstruction step needs to be increased for system-matrix approaches and for deconvolution steps in x-space approaches. To improve the signal-to-noise ratio, blockwise averaging of the signal over time can be advantageous. However, since block-wise averaging decreases the temporal resolution, it prevents resolving the motion. In this paper, a framework for averaging motion-corrupted MPI raw data is proposed. The motion is considered to be periodic as it is the case for respiration and/or the heartbeat. The same state of motion is thus reached repeatedly in a time series exceeding the repetition time of the motion and can be used for averaging. As the motion process and the acquisition process are, in general, not synchronized, averaging of the captured MPI raw data corresponding to the same state of motion requires to shift the starting point of the individual frames. For high-frequency motion, a higher frame rate is potentially required. To address this issue, a binning method for using only parts of complete frames from a motion cycle is proposed that further reduces the motion artifacts in the final images. The frequency of motion is derived directly from the MPI raw data signal without the need to capture an additional navigator signal. Using a motion phantom, it is shown that the proposed method is capable of averaging experimental data with reduced motion artifacts. The methods are further validated on in-vivo data from mouse experiments to compensate the heartbeat.de_DE
tuhh.publisher.doi10.1109/TMI.2017.2666740-
tuhh.publication.instituteBiomedizinische Bildgebung E-5de_DE
tuhh.publication.instituteMedizintechnische Systeme E-1de_DE
tuhh.type.opus(wissenschaftlicher) Artikel-
tuhh.institute.germanBiomedizinische Bildgebung E-5de
tuhh.institute.englishMedizintechnische Systeme E-1de_DE
tuhh.gvk.hasppnfalse-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.issue7de_DE
tuhh.container.volume36de_DE
tuhh.container.startpage1511de_DE
tuhh.container.endpage1521de_DE
dc.relation.projectGanzkörper Magnetic-Particle-Imaging Messsequenzen-
item.creatorGNDGdaniec, Nadine-
item.creatorGNDSchlüter, Matthias-
item.creatorGNDMöddel, Martin-
item.creatorGNDKaul, Michael-
item.creatorGNDKrishnan, Kannan M.-
item.creatorGNDSchlaefer, Alexander-
item.creatorGNDKnopp, Tobias-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.grantfulltextnone-
item.creatorOrcidGdaniec, Nadine-
item.creatorOrcidSchlüter, Matthias-
item.creatorOrcidMöddel, Martin-
item.creatorOrcidKaul, Michael-
item.creatorOrcidKrishnan, Kannan M.-
item.creatorOrcidSchlaefer, Alexander-
item.creatorOrcidKnopp, Tobias-
crisitem.author.deptBiomedizinische Bildgebung E-5-
crisitem.author.deptMedizintechnische Systeme E-1-
crisitem.author.deptBiomedizinische Bildgebung E-5-
crisitem.author.deptMedizintechnische Systeme E-1-
crisitem.author.deptBiomedizinische Bildgebung E-5-
crisitem.author.orcid0000-0002-5060-0683-
crisitem.author.orcid0000-0002-2019-1102-
crisitem.author.orcid0000-0002-4737-7863-
crisitem.author.orcid0000-0002-1589-8517-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.project.funderDeutsche Forschungsgemeinschaft (DFG)-
crisitem.project.funderid501100001659-
crisitem.project.funderrorid018mejw64-
crisitem.project.grantnoKN 1108/2-1-
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