DC shift based image reconstruction for magnetic particle imaging
buir.contributor.author | Sarıca, Damla | |
buir.contributor.author | Demirel, Ömer Burak | |
buir.contributor.author | Sarıtaş, Emine Ülkü | |
dc.contributor.author | Sarıca, Damla | en_US |
dc.contributor.author | Demirel, Ömer Burak | en_US |
dc.contributor.author | Sarıtaş, Emine Ülkü | en_US |
dc.coverage.spatial | Antalya, Turkey | en_US |
dc.date.accessioned | 2018-04-12T11:44:35Z | |
dc.date.available | 2018-04-12T11:44:35Z | |
dc.date.issued | 2017 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.department | National Magnetic Resonance Research Center (UMRAM) | en_US |
dc.department | Interdisciplinary Program in Neuroscience (NEUROSCIENCE) | en_US |
dc.department | Aysel Sabuncu Brain Research Center (BAM) | en_US |
dc.description | Date of Conference: 15-18 May 2017 | en_US |
dc.description | Conference Name: IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017 | en_US |
dc.description.abstract | Magnetic 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.provenance | Made 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: 2017 | en |
dc.identifier.doi | 10.1109/SIU.2017.7960614 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/37582 | |
dc.language.iso | Turkish | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/SIU.2017.7960614 | en_US |
dc.source.title | Proceedings of the IEEE 25th Signal Processing and Communications Applications Conference, SIU 2017 | en_US |
dc.subject | DC shift image | en_US |
dc.subject | Direct feedthrough | en_US |
dc.subject | Image reconstruction | en_US |
dc.subject | Magnetic particle imaging (MPI) | en_US |
dc.subject | Magnetic fields | en_US |
dc.subject | Nanomagnetics | en_US |
dc.subject | Nanoparticles | en_US |
dc.subject | Magnetic field strengths | en_US |
dc.subject | Magnetic particle imaging | en_US |
dc.title | DC shift based image reconstruction for magnetic particle imaging | en_US |
dc.title.alternative | Manyetik parçacık görüntüleme için DC kayma tabanlı görüntü geriçatımı | en_US |
dc.type | Conference Paper | en_US |
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