Jürß, PaulPaulJürßDroigk, ChristineChristineDroigkBoberg, MarijaMarijaBobergKnopp, TobiasTobiasKnopp2025-04-112025-04-112025-03-14International Journal on Magnetic Particle Imaging 11 (1, Suppl 1): 2503031 (2025)https://hdl.handle.net/11420/55323Large 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.en2365-903320251, Suppl 1Infinite Science Publishinghttps://creativecommons.org/licenses/by/4.0/Computer Science, Information and General Works::004: Computer SciencesTechnology::610: Medicine, HealthTechnology::621: Applied Physics::621.3: Electrical Engineering, Electronic EngineeringJournal Articlehttps://doi.org/10.15480/882.1506710.18416/ijmpi.2025.250303110.15480/882.15067Journal Article