Markus Bujotzek

According to our database, Markus Bujotzek authored at least 11 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation.

Tristan Kirscher, Markus Bujotzek, Yannick Kirchhoff, Maximilian Rokuss, Fabian Isensee, Kim-Celine Kahl, Balint Kovacs, Klaus Maier-Hein

CoRR, May, 2026

2025

Kaapana: A Comprehensive Open-Source Platform for Integrating AI in Medical Imaging Research Environments.

Ünal Akünal, Markus Bujotzek, Stefan Denner, Benjamin Hamm, Klaus Kades, Philipp Schader, Jonas Scherer, Marco Nolden, Peter Neher, Ralf Floca, Klaus H. Maier-Hein

CoRR, December, 2025

Insights into the Unknown: Federated Data Diversity Analysis on Molecular Data.

Markus Bujotzek, Evelyn Trautmann, Calum Hand, Ian Hales

CoRR, October, 2025

Real-world federated learning in radiology: hurdles to overcome and benefits to gain.

Markus R. Bujotzek, Ünal Akünal, Stefan Denner, Peter Neher, Maximilian Zenk, Eric Frodl, Astha Jaiswal, Moon S. Kim, Nicolai R. Krekiehn, Manuel Nickel, Richard Ruppel, Marcus Both, Felix Döllinger, Marcel Opitz, Thorsten Persigehl, Jens Kleesiek, Tobias Penzkofer, Klaus H. Maier-Hein, Andreas Bucher, Rickmer Braren

J. Am. Medical Informatics Assoc., 2025

Leveraging foundation models for content-based image retrieval in radiology.

Stefan Denner, David Zimmerer, Dimitrios Bounias, Markus Bujotzek, Shuhan Xiao, Raphael Stock, Lisa Kausch, Philipp Schader, Tobias Penzkofer, Paul F. Jäger, Klaus H. Maier-Hein

Comput. Biol. Medicine, 2025

Abstract: Real-world Federated Learning in Radiology - Hurdles to Overcome and Benefits to Gain.

Markus Bujotzek, Ünal Akünal, Stefan Denner, Peter Neher, Maximilian Zenk, Klaus H. Maier-Hein, Andreas Bucher, Rickmer Braren

Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

2024

Fair evaluation of federated learning algorithms for automated breast density classification: The results of the 2022 ACR-NCI-NVIDIA federated learning challenge.

Kendall Schmidt, Benjamin Bearce, Ken Chang, Laura Coombs, Keyvan Farahani, Marawan Elbatel, Kaouther Mouheb, Robert Marti, Ruipeng Zhang, Ya Zhang, Yanfeng Wang, Yaojun Hu, Haochao Ying, Yuyang Xu, Conrad Testagrose, Mutlu Demirer, Vikash Gupta, Ünal Akünal, Markus Bujotzek, Klaus H. Maier-Hein, Yi Qin, Xiaomeng Li, Jayashree Kalpathy-Cramer, Holger R. Roth

Medical Image Anal., 2024

Visual Prompt Engineering for Medical Vision Language Models in Radiology.

Stefan Denner, Markus Bujotzek, Dimitrios Bounias, David Zimmerer, Raphael Stock, Paul F. Jäger, Klaus H. Maier-Hein

CoRR, 2024

Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge.

Kendall Schmidt, Ben Bearce, Ken Chang, Laura Coombs, Keyvan Farahani, Marawan Elbatel, Kaouther Mouheb, Robert Marti, Ruipeng Zhang, Yao Zhang, Yanfeng Wang, Yaojun Hu, Haochao Ying, Yuyang Xu, Conrad Testagrose, Mutlu Demirer, Vikash Gupta, Ünal Akünal, Markus Bujotzek, Klaus H. Maier-Hein, Yi Qin, Xiaomeng Li, Jayashree Kalpathy-Cramer, Holger R. Roth

CoRR, 2024

Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology.

Stefan Denner, David Zimmerer, Dimitrios Bounias, Markus Bujotzek, Shuhan Xiao, Lisa Kausch, Philipp Schader, Tobias Penzkofer, Paul F. Jäger, Klaus H. Maier-Hein

CoRR, 2024

2023

Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications.

Stefan Denner, Jonas Scherer, Klaus Kades, Dimitrios Bounias, Philipp Schader, Lisa Kausch, Markus Bujotzek, Andreas Michael Bucher, Tobias Penzkofer, Klaus H. Maier-Hein

Proceedings of the Data Engineering in Medical Imaging - First MICCAI Workshop, 2023