International Journal on Magnetic Particle Imaging
Vol 8 No 1 (2022): Int J Mag Part Imag
https://doi.org/10.18416/IJMPI.2022.2208001

Research Articles

Improving Model-Based MPI Image Reconstructions: Baseline Recovery, Receive Coil Sensitivity, Relaxation and Uncertainty Estimation

Main Article Content

Mark-Alexander Henn  , Klaus Natorf Quelhas  (Instituto Nacional de Metrologia, Rio de Janeiro, Brazil), Thinh Q. Bui  (National Institute of Standards and Technology), Solomon I. Woods  (National Institute of Standards and Technology)

Abstract

Image reconstruction is an integral part of Magnetic Particle Imaging (MPI). Over the last years, several methods have been proposed for reconstructing MPI images more efficiently and accurately. One major challenge for model-based MPI image reconstruction methods is the realistic modeling of the measurement system; effects like non-linear gradient fields, non-uniform drive fields, space-dependent coil sensitivities, drive frequency filtering and particle relaxation, if not properly accounted for in the model, may yield inaccurate reconstructions. This work addresses these issues by means of an image reconstruction method that accounts for the coil sensitivity, baseline recovery and particle relaxation. We investigate the proposed approach for a 1D MPI setup, and provide an approach for the calculation of the uncertainties of the reconstructed images.
 
Int. J. Mag. Part. Imag. 8(1), 2022, Article ID: 2208001, DOI: 10.18416/IJMPI.2022.2208001

Article Details

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