Image reconstruction for Magnetic Particle Imaging using an Augmented Lagrangian Method
dc.citation.epage | 67 | en_US |
dc.citation.spage | 64 | en_US |
dc.contributor.author | Ilbey S. | en_US |
dc.contributor.author | Top C.B. | en_US |
dc.contributor.author | Çukur, Tolga | en_US |
dc.contributor.author | Sarıtaş, Emine Ülkü | en_US |
dc.contributor.author | Guven H.E. | en_US |
dc.coverage.spatial | Melbourne, VIC, Australia | en_US |
dc.date.accessioned | 2018-04-12T11:46:02Z | |
dc.date.available | 2018-04-12T11:46:02Z | |
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.description | Date of Conference: 18-21 April 2017 | en_US |
dc.description.abstract | Magnetic particle imaging (MPI) is a relatively new imaging modality that images the spatial distribution of superparamagnetic iron oxide nanoparticles administered to the body. In this study, we use a new method based on Alternating Direction Method of Multipliers (a subset of Augmented Lagrangian Methods, ADMM) with total variation and l1 norm minimization, to reconstruct MPI images. We demonstrate this method on data simulated for a field free line MPI system, and compare its performance against the conventional Algebraic Reconstruction Technique. The ADMM improves image quality as indicated by a higher structural similarity, for low signal-to-noise ratio datasets, and it significantly reduces computation time. © 2017 IEEE. | en_US |
dc.description.provenance | Made available in DSpace on 2018-04-12T11:46:02Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017 | en |
dc.identifier.doi | 10.1109/ISBI.2017.7950469 | en_US |
dc.identifier.isbn | 9781509011711 | |
dc.identifier.uri | http://hdl.handle.net/11693/37623 | |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/ISBI.2017.7950469 | en_US |
dc.source.title | 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) | en_US |
dc.subject | Algebraic reconstruction technique | en_US |
dc.subject | Alternating direction method of multipliers | en_US |
dc.subject | Augmented Lagrangian method | en_US |
dc.subject | Field free line | en_US |
dc.subject | Magnetic particle imaging | en_US |
dc.subject | Algebra | en_US |
dc.subject | Constrained optimization | en_US |
dc.subject | Image processing | en_US |
dc.subject | Lagrange multipliers | en_US |
dc.subject | Magnetism | en_US |
dc.subject | Medical imaging | en_US |
dc.subject | Nanomagnetics | en_US |
dc.subject | Optimization | en_US |
dc.subject | Signal to noise ratio | en_US |
dc.subject | Algebraic reconstruction techniques | en_US |
dc.subject | Alternating direction method of multipliers | en_US |
dc.subject | Augmented Lagrangian methods | en_US |
dc.subject | Field free line | en_US |
dc.subject | Magnetic particle imaging | en_US |
dc.subject | Image reconstruction | en_US |
dc.title | Image reconstruction for Magnetic Particle Imaging using an Augmented Lagrangian Method | en_US |
dc.type | Conference Paper | en_US |
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