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2020 – today
- 2024
[i4]Jonas Weidner, Ivan Ezhov, Michal Balcerak, Marie-Christin Metz, Sergey Litvinov, Sebastian Kaltenbach, Leonhard F. Feiner, Laurin Lux, Florian Kofler, Jana Lipková, Jonas Latz, Daniel Rueckert, Bjoern H. Menze, Benedikt Wiestler:
A Learnable Prior Improves Inverse Tumor Growth Modeling. CoRR abs/2403.04500 (2024)- 2023
- [c2]Leonhard F. Feiner
, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis:
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. UNSURE@MICCAI 2023: 1-11 - [c1]Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis:
Extended Graph Assessment Metrics for Regression and Weighted Graphs. GRAIL/OCELOT@MICCAI 2023: 14-26 - [i3]Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner, Kyriaki-Margarita Bintsi, Daniel Rueckert, Georgios Kaissis:
Extended Graph Assessment Metrics for Graph Neural Networks. CoRR abs/2307.10112 (2023) - [i2]Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis:
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. CoRR abs/2309.16831 (2023) - [i1]Alexander Ziller, Tamara T. Mueller, Simon Stieger, Leonhard F. Feiner, Johannes Brandt, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging. CoRR abs/2312.04590 (2023)
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