Deep Learning-Based Anonymization of Chest Radiographs: A Utility-Preserving Measure for Patient Privacy

Packhäuser K, Gündel S, Thamm F, Denzinger F, Maier A (2023)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2023

Publisher: Springer

City/Town: Cham

Conference Proceedings Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

Event location: Vancouver

ISBN: 978-3-031-43898-1

DOI: 10.1007/978-3-031-43898-1_26

Authors with CRIS profile

How to cite

APA:

Packhäuser, K., Gündel, S., Thamm, F., Denzinger, F., & Maier, A. (2023). Deep Learning-Based Anonymization of Chest Radiographs: A Utility-Preserving Measure for Patient Privacy. In Greenspan H, Madabhushi A, Mousavi P, Salcudean S, Duncan J, Syeda-Mahmood T, Taylor R (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. Vancouver, CA: Cham: Springer.

MLA:

Packhäuser, Kai, et al. "Deep Learning-Based Anonymization of Chest Radiographs: A Utility-Preserving Measure for Patient Privacy." Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention – MICCAI 2023, Vancouver Ed. Greenspan H, Madabhushi A, Mousavi P, Salcudean S, Duncan J, Syeda-Mahmood T, Taylor R, Cham: Springer, 2023.

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