Manyetik parçacık görüntüleme için sinyal-gürültü oranını eniyileyen görüntü geriçatım tekniği

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buir.contributor.authorBozkurt, Ecem
buir.contributor.authorSarıtaş, Emine Ülkü
dc.citation.epage1013en_US
dc.citation.issueNumber3en_US
dc.citation.spage999en_US
dc.citation.volumeNumber32en_US
dc.contributor.authorBozkurt, Ecemen_US
dc.contributor.authorSarıtaş, Emine Ülküen_US
dc.date.accessioned2018-04-12T10:59:53Z
dc.date.available2018-04-12T10:59:53Z
dc.date.issued2017en_US
dc.departmentNational Magnetic Resonance Research Center (UMRAM)en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentInterdisciplinary Program in Neuroscience (NEUROSCIENCE)en_US
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.description.abstractMagnetic particle imaging (MPI) is a new biomedical imaging modality that images the spatial distribution of superpamagnetic iron oxide nanoparticles. In MPI, the amplitude of the excitation magnetic field that causes the time-varying magnetization response of the nanoparticles is restricted by the nerve stimulation safety limits. Hence, the region to be imaged is divided into small sections and scanned as overlapping partial fields-of-view. The nanoparticle signal at the excitation frequency is lost during the filtering process of the direct feedthrough signal induced on the receive coil due to the excitation field. To recover this loss, the overlapping partial fields-of-view are merged via utilizing the continuity and positivity of the desired image. In this work, an image reconstruction technique that merges the partial fields-of-view while optimizing the signal-to-noise ratio is proposed. Accordingly, each partial field-of-view must be weighted by the square of the position-dependent scanning speed. Via extensive simulations at various overlap percentages and signal-to-noise ratios, this work demonstrates that the proposed method overcomes the vertical line artifacts caused by the standard MPI reconstruction techniques and improves image quality.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T10:59:53Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017en
dc.identifier.doi10.17341/gazimmfd.337864en_US
dc.identifier.issn1300-1884
dc.identifier.urihttp://hdl.handle.net/11693/37009
dc.language.isoTurkishen_US
dc.publisherGazi Universitesi Muhendislik-Mimarliken_US
dc.relation.isversionofhttp://dx.doi.org/10.17341/gazimmfd.337864en_US
dc.source.titleJournal of the Faculty of Engineering and Architecture of Gazi Universityen_US
dc.subjectAngiographyen_US
dc.subjectImage reconstructionen_US
dc.subjectMagnetic particle imagingen_US
dc.subjectSignal-to-noise ratioen_US
dc.subjectSuperparamagnetic iron oxide nanoparticlesen_US
dc.titleManyetik parçacık görüntüleme için sinyal-gürültü oranını eniyileyen görüntü geriçatım tekniğien_US
dc.title.alternativeSignal-to-noise ratio optimized image reconstruction technique for magnetic particle imagingen_US
dc.typeArticleen_US

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