Fast system calibration with coded calibration scenes for magnetic particle imaging

Simple item page
buir.contributor.authorİlbey, Serhat
buir.contributor.authorGüngör, Alper
buir.contributor.authorÇukur, Tolga
buir.contributor.authorSarıtaş, Emine Ülkü
buir.contributor.authorGüven, H. Emre
dc.citation.epage2080en_US
dc.citation.issueNumber9en_US
dc.citation.spage2070en_US
dc.citation.volumeNumber38en_US
dc.contributor.authorİlbey, Serhat
dc.contributor.authorTop, C. B.
dc.contributor.authorGüngör, Alper
dc.contributor.authorÇukur, Tolga
dc.contributor.authorSarıtaş, Emine Ülkü
dc.contributor.authorGüven, H. Emre
dc.date.accessioned2021-03-10T07:07:58Z
dc.date.available2021-03-10T07:07:58Z
dc.date.issued2019
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentInterdisciplinary Program in Neuroscience (NEUROSCIENCE)en_US
dc.departmentNational Magnetic Resonance Research Center (UMRAM)en_US
dc.description.abstractMagnetic particle imaging (MPI) is a relatively new medical imaging modality, which detects the nonlinear response of magnetic nanoparticles (MNPs) that are exposed to external magnetic fields. The system matrix (SM) method for MPI image reconstruction requires a time consuming system calibration scan prior to image acquisition, where a single MNP sample is measured at each voxel position in the field-of-view (FOV). The scanned sample has the maximum size of a voxel so that the calibration measurements have relatively poor signal-to-noise ratio (SNR). In this paper, we present the coded calibration scene (CCS) framework, where we place multiple MNP samples inside the FOV in a random or pseudo-random fashion. Taking advantage of the sparsity of the SM, we reconstruct the SM by solving a convex optimization problem with alternating direction method of multipliers using CCS measurements. We analyze the effects of filling rate, number of measurements, and SNR on the SM reconstruction using simulations and demonstrate different implementations of CCS for practical realization. We also compare the imaging performance of the proposed framework with that of a standard compressed sensing SM reconstruction that utilizes a subset of calibration measurements from a single MNP sample. The results show that CCS significantly reduces calibration time while increasing both the SM reconstruction and image reconstruction performances.en_US
dc.description.sponsorshipThis work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 9050103 and Grant 115E677. The work of E. U. Saritas and T. Çukur was supported in part by the Turkish Academy of Sciences through the TUBA-GEBIP 2015 Program, in part by the BAGEP Award of the Science Academy, and in part by the European Molecular Biology Organization through an Installation Grant 3028.en_US
dc.identifier.doi10.1109/TMI.2019.2896289en_US
dc.identifier.issn0278-0062
dc.identifier.urihttp://hdl.handle.net/11693/75906
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://dx.doi.org/10.1109/TMI.2019.2896289en_US
dc.source.titleIEEE Transactions on Medical Imagingen_US
dc.subjectMagnetic particle imagingen_US
dc.subjectSystem matrixen_US
dc.subjectCompressed sensingen_US
dc.subjectAlternating direction method of multipliersen_US
dc.subjectCoded calibration scenesen_US
dc.subjectCalibrationen_US
dc.titleFast system calibration with coded calibration scenes for magnetic particle imagingen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Fast_System_Calibration_With_Coded_Calibration_Scenes_for_Magnetic_Particle_Imaging.pdf
Size:
3.03 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
National Magnetic Resonance Research Center (UMRAM)
Aysel Sabuncu Brain Research Center (BAM)
Department of Electrical and Electronics Engineering