International Journal on Magnetic Particle Imaging IJMPI
Vol. 9 No. 1 Suppl 1 (2023): Int J Mag Part Imag
https://doi.org/10.18416/IJMPI.2023.2303008

Proceedings Articles

A Deep Learning Approach for Automatic Image Reconstruction in MPI

Main Article Content

Tobias Knopp , Paul Jürß (Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany), Mirco Grosser (Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany)

Abstract

Image reconstruction in magnetic particle imaging is a challenging task because the optimal image quality can only be obtained by tuning the reconstruction parameters for each measurement individually. In particular, it requires a proper selection of the Tikhonov regularization parameter. In this work we propose a deep-learning-based post-processing technique, which removes the need for manual parameter optimization. The proposed neural network takes several images reconstructed with different parameters as input and combines them into a single high-quality image.

Article Details

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