DC shift based image reconstruction for magnetic particle imaging

buir.contributor.authorSarıca, Damla
buir.contributor.authorDemirel, Ömer Burak
buir.contributor.authorSarıtaş, Emine Ülkü
dc.contributor.authorSarıca, Damlaen_US
dc.contributor.authorDemirel, Ömer Buraken_US
dc.contributor.authorSarıtaş, Emine Ülküen_US
dc.coverage.spatialAntalya, Turkeyen_US
dc.date.accessioned2018-04-12T11:44:35Z
dc.date.available2018-04-12T11:44:35Z
dc.date.issued2017en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentNational Magnetic Resonance Research Center (UMRAM)en_US
dc.departmentInterdisciplinary Program in Neuroscience (NEUROSCIENCE)en_US
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.descriptionDate of Conference: 15-18 May 2017en_US
dc.descriptionConference Name: IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017en_US
dc.description.abstractMagnetic Particle Imaging (MPI) is a new imaging technology that images the spatial distribution of iron oxide nanoparticles. Since the magnetic field strength that can be safely applied in MPI is limited, the field-of-view (FOV) must be divided into partial FOVs. Because the excitation magnetic field causes direct feedthrough on the receiver coil, the excitation frequency must be filtered out of the MPI signal. During this process, the nanoparticle signal at the same frequency is also lost, as a result of which each partial FOV experiences different levels of DC shift. In the standard MPI image reconstruction, these DC shifts are calculated from neighboring overlapping partial FOVs. Here, we propose a novel method that directly reconstructs the MPI image from the calculated DC shift values. Especially in the case of low bandwidth signal acquisitions, this method yields higher resolution images when compared to the standard method. The simulation results at various signal-to-noise ratios (SNR) show that the proposed method produces 6-8 dB increase in peak SNR and yields images that closely match the ideal image.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T11:44:35Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017en
dc.identifier.doi10.1109/SIU.2017.7960614en_US
dc.identifier.urihttp://hdl.handle.net/11693/37582
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2017.7960614en_US
dc.source.titleProceedings of the IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017en_US
dc.subjectDC shift imageen_US
dc.subjectDirect feedthroughen_US
dc.subjectImage reconstructionen_US
dc.subjectMagnetic particle imaging (MPI)en_US
dc.subjectMagnetic fieldsen_US
dc.subjectNanomagneticsen_US
dc.subjectNanoparticlesen_US
dc.subjectMagnetic field strengthsen_US
dc.subjectMagnetic particle imagingen_US
dc.titleDC shift based image reconstruction for magnetic particle imagingen_US
dc.title.alternativeManyetik parçacık görüntüleme için DC kayma tabanlı görüntü geriçatımıen_US
dc.typeConference Paperen_US

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