Style Transfer as Data Augmentation: Evaluating Unpaired Image-to-Image Translation Models in Mammography

Posted on by Alessandra

10/07/2026

Style Transfer as Data Augmentation: Evaluating Unpaired Image-to-Image Translation Models in Mammography

E. Ahmed1, S. A. Thomas1  and C. Bench1
1Department of Data Science and AI, National Physical Laboratory, Teddington, United Kingdom

Style Transfer as Data Augmentation: Evaluating Unpaired Image-to-Image Translation Models in Mammography in 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, 2025, pp. 1-7

doi: 10.1109/EMBC58623.2025.11253212

https://arxiv.org/abs/2502.02475

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The project 22HLT05 MAIBAI, started in September 2023, has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States. Funding for the UK partners is provided by Innovate UK under the Horizon Europe Guarantee Extension.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or EURAMET. Neither the European Union nor the granting authority can be held responsible for them.

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