International Journal on Magnetic Particle Imaging IJMPI
Vol. 11 No. 1 Suppl 1 (2025): Int J Mag Part Imag
https://doi.org/10.18416/IJMPI.2025.2503031

Proceedings Articles

TrainingPhantoms.jl: Simple and Versatile Image Phantom Generation

Main Article Content

Paul Jürß (University Medical Center Hamburg-Eppendorf; Hamburg University of Technology), Christine Droigk (Institute for Signal Processing, University of Lübeck, Lübeck, Germany), Marija Boberg (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany), Tobias Knopp (1) Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 2) Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany; 3) Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering IMTE, Lübeck, Germany)

Copyright (c) 2025 Paul Jürß, Christine Droigk, Marija Boberg, Tobias Knopp

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Large collections of labeled data play a crucial role in supervised machine learning projects. Unfortunately, such datasets are quite rare in the medical domain. In this work, the Julia project TrainingPhantoms.jl is introduced, which provides a simple interface to generate large and diverse collections of randomly generated image phantoms. The proposed phantom generator has been successfully used to train an image quality enhancement network that managed to generalize to unseen experimental out-of-distribution data.

Article Details

References

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