Improving the fairness and robustness of deep learning classification models through bias mitigation and post hoc calibration

Majid Ramedani, Jaya C. Terli, Ole H. Martensen, Tobias Strauß, Katharina Buerger, Peter Dechent, Emrah Düzel, Klaus Fliessbach, Maria Gemenetzi, Wenzel Glanz, Julian Hellmann-Regen, Stefan Hetzer, Enise I. Incesoy, Daniel Janowitz, Marie T. Kronmüller, Christoph Laske, Falk Lüsebrink, Robert Perneczky, Oliver Peters, Lukas Preis, Josef Priller, Boris-Stephan Rauchmann, Ayda Rostamzadeh, Anja Schneider, Björn H. Schott, Sebastian Sodenkamp, Annika Spottke, Eike J. Spruth, Sophia Stöcklein, Jens Wiltfang, Frank Jessen, Stefan J. Teipel, Martin Dyrba

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DOI: 10.1007/s11548-026-03805-x
Published: 2026-10-17
Container: International Journal of Computer Assisted Radiology and Surgery
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s11548-026-03805-x,
  title = {Improving the fairness and robustness of deep learning classification models through bias mitigation and post hoc calibration},
  author = {Majid Ramedani and Jaya C. Terli and Ole H. Martensen and Tobias Strauß and Katharina Buerger and Peter Dechent and Emrah Düzel and Klaus Fliessbach and Maria Gemenetzi and Wenzel Glanz and Julian Hellmann-Regen and Stefan Hetzer and Enise I. Incesoy and Daniel Janowitz and Marie T. Kronmüller and Christoph Laske and Falk Lüsebrink and Robert Perneczky and Oliver Peters and Lukas Preis and Josef Priller and Boris-Stephan Rauchmann and Ayda Rostamzadeh and Anja Schneider and Björn H. Schott and Sebastian Sodenkamp and Annika Spottke and Eike J. Spruth and Sophia Stöcklein and Jens Wiltfang and Frank Jessen and Stefan J. Teipel and Martin Dyrba},
  year = {2026},
  journal = {International Journal of Computer Assisted Radiology and Surgery},
  doi = {10.1007/s11548-026-03805-x},
  url = {https://doi.org/10.1007/s11548-026-03805-x}
}

RIS

TY  - JOUR
TI  - Improving the fairness and robustness of deep learning classification models through bias mitigation and post hoc calibration
AU  - Majid Ramedani
AU  - Jaya C. Terli
AU  - Ole H. Martensen
AU  - Tobias Strauß
AU  - Katharina Buerger
AU  - Peter Dechent
AU  - Emrah Düzel
AU  - Klaus Fliessbach
AU  - Maria Gemenetzi
AU  - Wenzel Glanz
AU  - Julian Hellmann-Regen
AU  - Stefan Hetzer
AU  - Enise I. Incesoy
AU  - Daniel Janowitz
AU  - Marie T. Kronmüller
AU  - Christoph Laske
AU  - Falk Lüsebrink
AU  - Robert Perneczky
AU  - Oliver Peters
AU  - Lukas Preis
AU  - Josef Priller
AU  - Boris-Stephan Rauchmann
AU  - Ayda Rostamzadeh
AU  - Anja Schneider
AU  - Björn H. Schott
AU  - Sebastian Sodenkamp
AU  - Annika Spottke
AU  - Eike J. Spruth
AU  - Sophia Stöcklein
AU  - Jens Wiltfang
AU  - Frank Jessen
AU  - Stefan J. Teipel
AU  - Martin Dyrba
PY  - 2026
JO  - International Journal of Computer Assisted Radiology and Surgery
DO  - 10.1007/s11548-026-03805-x
UR  - https://doi.org/10.1007/s11548-026-03805-x
ER  -

APA

Ramedani, M., Terli, J. C., Martensen, O. H., Strauß, T., Buerger, K., Dechent, P., Düzel, E., Fliessbach, K., Gemenetzi, M., Glanz, W., Hellmann-Regen, J., Hetzer, S., Incesoy, E. I., Janowitz, D., Kronmüller, M. T., Laske, C., Lüsebrink, F., Perneczky, R., Peters, O., Preis, L., Priller, J., Rauchmann, B., Rostamzadeh, A., Schneider, A., Schott, B. H., Sodenkamp, S., Spottke, A., Spruth, E. J., Stöcklein, S., Wiltfang, J., Jessen, F., Teipel, S. J., & Dyrba, M. (2026). Improving the fairness and robustness of deep learning classification models through bias mitigation and post hoc calibration. International Journal of Computer Assisted Radiology and Surgery. https://doi.org/10.1007/s11548-026-03805-x

Source records

crossref · retrieved 2026-11-10T12:01:46.572Z