Teuwen, Jonas

Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 394

Results of the 2020 fastMRI challenge for machine learning MR image reconstruction

Muckley, M. J., Riemenschneider, B., Radmanesh, A., Kim, S., Jeong, G., Ko, J., Jun, Y., Shin, H., Hwang, D., Mostapha, M., et al. (2021) · IEEE Transactions on Medical Imaging

Advanced MRI Techniques and ApplicationsMedical Imaging Techniques and Applications

Cited by 313

Artificial Intelligence–Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI

Dalmiş, M. U., Gubern-Mérida, A., Vreemann, S., Bult, P., Karssemeijer, N., Mann, R., & Teuwen, J. (2019) · Investigative Radiology

MRI in cancer diagnosisAI in cancer detection

Cited by 120

Improving Breast Cancer Detection Using Symmetry Information with Deep Learning

Brhane Hagos, Y., Gubern Mérida, A., & Teuwen, J. (2018) · Lecture Notes in Computer Science

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 27

Towards Robust Foundation Models for Digital Pathology

Kömen, J., de Jong, E. D., Hense, J., Marienwald, H., Dippel, J., Naumann, P., Marcus, E., Ruff, L., Alber, M., Teuwen, J., et al. (2025) · arXiv

AI in cancer detectionArtificial Intelligence in Healthcare and Education

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Current Pathology Foundation Models are unrobust to Medical Center Differences

de Jong, E. D., Marcus, E., & Teuwen, J. (2025) · arXiv

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 7