A wavelet-based sparse row-action method for image reconstruction in magnetic particle imaging
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A wavelet-based sparse row-action method for image reconstruction in magnetic particle imaging. / Lieb, Florian; Knopp, Tobias.
in: MED PHYS, Jahrgang 48, Nr. 7, 07.2021, S. 3893-3903.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - A wavelet-based sparse row-action method for image reconstruction in magnetic particle imaging
AU - Lieb, Florian
AU - Knopp, Tobias
N1 - © 2021 American Association of Physicists in Medicine.
PY - 2021/7
Y1 - 2021/7
N2 - PURPOSE: Magnetic particle imaging (MPI) is a preclinical imaging technique capable of visualizing the spatio-temporal distribution of magnetic nanoparticles. The image reconstruction of this fast and dynamic process relies on efficiently solving an ill-posed inverse problem. Current approaches to reconstruct the tracer concentration from its measurements are either adapted to image characteristics of MPI but suffer from higher computational complexity and slower convergence or are fast but lack in the image quality of the reconstructed images.METHODS: In this work we propose a novel MPI reconstruction method to combine the advantages of both approaches into a single algorithm. The underlying sparsity prior is based on an undecimated wavelet transform and is integrated into a fast row-action framework to solve the corresponding MPI minimization problem.RESULTS: Its performance is numerically evaluated against a classical FISTA (Fast Iterative Shrinkage-Thresholding Algorithm) approach on simulated and real MPI data. The experimental results show that the proposed method increases image quality with significantly reduced computation times.CONCLUSIONS: In comparison to state-of-the-art MPI reconstruction methods, our approach shows better reconstruction results and at the same time accelerates the convergence rate of the underlying row-action algorithm.
AB - PURPOSE: Magnetic particle imaging (MPI) is a preclinical imaging technique capable of visualizing the spatio-temporal distribution of magnetic nanoparticles. The image reconstruction of this fast and dynamic process relies on efficiently solving an ill-posed inverse problem. Current approaches to reconstruct the tracer concentration from its measurements are either adapted to image characteristics of MPI but suffer from higher computational complexity and slower convergence or are fast but lack in the image quality of the reconstructed images.METHODS: In this work we propose a novel MPI reconstruction method to combine the advantages of both approaches into a single algorithm. The underlying sparsity prior is based on an undecimated wavelet transform and is integrated into a fast row-action framework to solve the corresponding MPI minimization problem.RESULTS: Its performance is numerically evaluated against a classical FISTA (Fast Iterative Shrinkage-Thresholding Algorithm) approach on simulated and real MPI data. The experimental results show that the proposed method increases image quality with significantly reduced computation times.CONCLUSIONS: In comparison to state-of-the-art MPI reconstruction methods, our approach shows better reconstruction results and at the same time accelerates the convergence rate of the underlying row-action algorithm.
KW - Algorithms
KW - Diagnostic Imaging
KW - Image Processing, Computer-Assisted
KW - Magnetic Phenomena
KW - Magnetic Resonance Imaging
KW - Phantoms, Imaging
KW - Wavelet Analysis
U2 - 10.1002/mp.14938
DO - 10.1002/mp.14938
M3 - SCORING: Journal article
C2 - 33982810
VL - 48
SP - 3893
EP - 3903
JO - MED PHYS
JF - MED PHYS
SN - 0094-2405
IS - 7
ER -