Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement
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Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement. / Boberg, Marija; Gdaniec, Nadine; Szwargulski, Patryk; Werner, Franziska; Möddel, Martin; Knopp, Tobias.
in: PHYS MED BIOL, Jahrgang 66, Nr. 9, 095004, 23.04.2021.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Simultaneous imaging of widely differing particle concentrations in MPI: problem statement and algorithmic proposal for improvement
AU - Boberg, Marija
AU - Gdaniec, Nadine
AU - Szwargulski, Patryk
AU - Werner, Franziska
AU - Möddel, Martin
AU - Knopp, Tobias
N1 - © 2021 Institute of Physics and Engineering in Medicine.
PY - 2021/4/23
Y1 - 2021/4/23
N2 - Magnetic particle imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system 'shadows' nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.
AB - Magnetic particle imaging (MPI) is a tomographic imaging technique for determining the spatial distribution of superparamagnetic nanoparticles. Current MPI systems are capable of imaging iron masses over a wide dynamic range of more than four orders of magnitude. In theory, this range could be further increased using adaptive amplifiers, which prevent signal clipping. While this applies to a single sample, the dynamic range is severely limited if several samples with different concentrations or strongly inhomogeneous particle distributions are considered. One scenario that occurs quite frequently in pre-clinical applications is that a highly concentrated tracer bolus in the vascular system 'shadows' nearby organs with lower effective tracer concentrations. The root cause of the problem is the ill-posedness of the MPI imaging operator, which requires regularization for stable reconstruction. In this work, we introduce a simple two-step algorithm that increases the dynamic range by a factor of four. Furthermore, the algorithm enables spatially adaptive regularization, i.e. highly concentrated signals can be reconstructed with maximum spatial resolution, while low concentrated signals are strongly regularized to prevent noise amplification.
KW - Algorithms
KW - Magnetite Nanoparticles
KW - Tomography
U2 - 10.1088/1361-6560/abf202
DO - 10.1088/1361-6560/abf202
M3 - SCORING: Journal article
C2 - 33765669
VL - 66
JO - PHYS MED BIOL
JF - PHYS MED BIOL
SN - 0031-9155
IS - 9
M1 - 095004
ER -