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Uncertainty estimation for 2D magnetic particle imaging

Published

Author(s)

Mark-Alexander Henn, Klaus Natorf Quelhas, Solomon I. Woods

Abstract

Magnetic Particle Imaging (MPI) has in recent years been established as a powerful imaging tool that measures thenon-linear magnetic response of magnetic particles to an applied field. Obtaining quantitative information fromthese images in the form of a discretized version of the particle distribution in space requires the solution of aninverse problem that can be addressed by linear regression. We demonstrate how the linear regression can be usedto also estimate the uncertainty of the reconstructed particle distribution.
Citation
International Journal on Magnetic Particle Imaging
Volume
8
Issue
1

Keywords

Magnetic Particle Imaging, Uncertainty Quantification, Simulation, Modelling

Citation

Henn, M. , Natorf Quelhas, K. and Woods, S. (2022), Uncertainty estimation for 2D magnetic particle imaging, International Journal on Magnetic Particle Imaging, [online], https://doi.org/10.18416/IJMPI.2022.2203082, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933967 (Accessed July 14, 2024)

Issues

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Created March 21, 2022, Updated November 29, 2022