Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.2368
DC FieldValueLanguage
dc.contributor.authorKnopp, Tobias-
dc.contributor.authorWeber, Alexander-
dc.date.accessioned2019-08-12T11:46:33Z-
dc.date.available2019-08-12T11:46:33Z-
dc.date.issued2015-
dc.identifier.citationAdvances in Mathematical Physics (2015): 472818 (2015)de_DE
dc.identifier.issn1687-9139de_DE
dc.identifier.urihttp://hdl.handle.net/11420/3092-
dc.description.abstractMagnetic particle imaging (MPI) is a quantitative method for determining the spatial distribution of magnetic nanoparticles, which can be used as tracers for cardiovascular imaging. For reconstructing a spatial map of the particle distribution, the system matrix describing the magnetic particle imaging equation has to be known. Due to the complex dynamic behavior of the magnetic particles, the system matrix is commonly measured in a calibration procedure. In order to speed up the reconstruction process, recently, a matrix compression technique has been proposed that makes use of a basis transformation in order to compress the MPI system matrix. By thresholding the resulting matrix and storing the remaining entries in compressed row storage format, only a fraction of the data has to be processed when reconstructing the particle distribution. In the present work, it is shown that the image quality of the algorithm can be considerably improved by using a local threshold for each matrix row instead of a global threshold for the entire system matrix.en
dc.language.isoende_DE
dc.publisherHindawide_DE
dc.relation.ispartofAdvances in mathematical physicsde_DE
dc.rightsCC BY 3.0de_DE
dc.subject.ddc530: Physikde_DE
dc.titleLocal system matrix compression for efficient reconstruction in magnetic particle imagingde_DE
dc.typeArticlede_DE
dc.identifier.urnurn:nbn:de:gbv:830-882.045382-
dc.identifier.doi10.15480/882.2368-
dc.type.diniarticle-
dc.subject.ddccode530-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.045382-
tuhh.oai.showtruede_DE
tuhh.abstract.englishMagnetic particle imaging (MPI) is a quantitative method for determining the spatial distribution of magnetic nanoparticles, which can be used as tracers for cardiovascular imaging. For reconstructing a spatial map of the particle distribution, the system matrix describing the magnetic particle imaging equation has to be known. Due to the complex dynamic behavior of the magnetic particles, the system matrix is commonly measured in a calibration procedure. In order to speed up the reconstruction process, recently, a matrix compression technique has been proposed that makes use of a basis transformation in order to compress the MPI system matrix. By thresholding the resulting matrix and storing the remaining entries in compressed row storage format, only a fraction of the data has to be processed when reconstructing the particle distribution. In the present work, it is shown that the image quality of the algorithm can be considerably improved by using a local threshold for each matrix row instead of a global threshold for the entire system matrix.de_DE
tuhh.publisher.doi10.1155/2015/472818-
tuhh.publication.instituteBiomedizinische Bildgebung E-5de_DE
tuhh.identifier.doi10.15480/882.2368-
tuhh.type.opus(wissenschaftlicher) Artikel-
tuhh.institute.germanBiomedizinische Bildgebung E-5de
tuhh.institute.englishBiomedizinische Bildgebung E-5de_DE
tuhh.gvk.hasppnfalse-
dc.type.driverarticle-
dc.rights.cchttps://creativecommons.org/licenses/by/3.0/de_DE
dc.type.casraiJournal Article-
tuhh.container.volume2015de_DE
tuhh.container.startpage1de_DE
tuhh.container.endpage7de_DE
dc.rights.nationallicensefalsede_DE
tuhh.container.articlenumber472818de_DE
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextWith Fulltext-
item.creatorGNDKnopp, Tobias-
item.creatorGNDWeber, Alexander-
item.grantfulltextopen-
item.creatorOrcidKnopp, Tobias-
item.creatorOrcidWeber, Alexander-
item.openairetypeArticle-
item.languageiso639-1en-
crisitem.author.deptBiomedizinische Bildgebung E-5-
crisitem.author.orcid0000-0002-1589-8517-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
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