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  4. A deep learning approach for automatic image reconstruction in MPI
 
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A deep learning approach for automatic image reconstruction in MPI

Citation Link: https://doi.org/10.15480/882.5064
Publikationstyp
Journal Article
Date Issued
2023-03-19
Sprache
English
Author(s)
Knopp, Tobias  
Jürß, Paul  
Grosser, Mirco  
Institut
Biomedizinische Bildgebung E-5  
TORE-DOI
10.15480/882.5064
TORE-URI
http://hdl.handle.net/11420/15192
Journal
International journal on magnetic particle imaging  
Volume
9
Issue
1, suppl. 1
Article Number
2303008
Citation
International Journal on Magnetic Particle Imaging 9 (1, suppl. 1): 2303008 (2023)
Publisher DOI
10.18416/IJMPI.2023.2303008
Scopus ID
2-s2.0-85151463443
Publisher
Infinite Science Publishing
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.
DDC Class
004: Informatik
600: Technik
620: Ingenieurwissenschaften
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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