Fraunhofer Institute for Digital Medicine MEVIS
Fraunhofer Institute for Digital Medicine MEVIS

Dr.-Ing. Eike Petersen

Research Interests

  • Medical AI robustness and generalization
  • AI evaluation, certification, regulation, quality assurance
  • AI bias and fairness (also see FAIMI) 
  • Uncertainty quantification, statistical inference
  • XAI
  • Data & AI Readiness

Publications

(Tba)

2025

Basso L, Ahmadi Z, Oeltze-Jafra S, Petersen E, Shin H, Schenk A (2025) Using Photon-Counting CT Images for Lung Nodule Classification. Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, pp 1102–1103
doi
Dornbusch S, Schenk A, Petersen E, Fehling R, Lenzen H, Levers A, Winther H, Wacker F, Ringe K (2025) Stellenwert der MRT als prognostischer Langzeitbiomarker bei Patienten mit primär sklerosierender Cholangitis (PSC). RöFo – Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 197(S01):15–16
doi
Olesen V, Weng N, Feragen A, Petersen E (2025) Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis Using Slice Discovery Methods. In: Puyol-Antón E et al (ed) Ethics and Fairness in Medical Imaging. FAIMI 2024 EPIMI 2024. LNCS, pp 3–13
doi
Pedersen N, Sydendal R, Wulff A, Raumanns R, Petersen E, Cheplygina V (2025) Robustness and Sex Differences in Skin Cancer Detection: Logistic Regression vs CNNs. In: Puyol-Antón E, et al (eds) Fairness of AI in Medical Imaging 2025. LNCS, pp 115–124
doi
Petersen E, Ursin F (2025) Against Disease Classification: Toward Continuous Disease Assessment in Precision Medicine. NEJM AI 3(1)
doi
Sutariya D, Petersen E (2025) meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis. MICCAI Workshop on Fairness of AI in Medical Imaging (FAIMI). pp 187–197
doi

2024

Olesen V, Weng N, Feragen A, Petersen E (2024) Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis Using Slice Discovery Methods. MICCAI Workshop on Fairness of AI in Medical Imaging (FAIMI). pp 3–13
doi

2022

Petersen E, Potdevin Y, Mohammadi E, Zidowitz S, Breyer S, Nowotka D, Henn S, Pechmann L, Leucker M, Rostalski P, Herzog C (2022) Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions. IEEE Access 10:58375–58418
doi

2015

Mutsaerts HJMM, van Osch MJP, Zelaya FO, Wang DJJ, Nordhøy W, Wang Y, Wastling S, Fernandez-Seara MA, Petersen ET, Pizzini FB, Fallatah S, Hendrikse J, Geier O, Guenther M, Golay X, Nederveen AJ, Bjørnerud A, Groote IR (2015) Multi-vendor reliability of arterial spin labeling perfusion MRI using a near-identical sequence: Implications for multi-center studies. NeuroImage 113:143–152
doi