A deep learning approach for automatic image reconstruction in MPI

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.

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004: Informatik

600: Technik

620: Ingenieurwissenschaften

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https://creativecommons.org/licenses/by/4.0/

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517-Article Text-3569-1-10-20230320.pdf

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A deep learning approach for automatic image reconstruction in MPI