Efficient, high-performance pancreatic segmentation using multi-scale feature extraction. - Moritz Knolle; Georgios Kaissis; Friederike Jungmann; Sebastian Ziegelmayer; Daniel Sasse; Marcus R. Makowski; Daniel Rueckert; Rickmer Braren (CoRR, 2020)

Privacy-preserving medical image analysis. - Alexander Ziller; Jonathan Passerat-Palmbach; Théo Ryffel; Dmitrii Usynin; Andrew Trask; Ionésio Da Lima Costa Junior; Jason Mancuso; Marcus R. Makowski; Daniel Rueckert; Rickmer Braren; Georgios Kaissis (CoRR, 2020)

Secure, privacy-preserving and federated machine learning in medical imaging. - Georgios Kaissis; Marcus R. Makowski; Daniel Rueckert; Rickmer Braren (Nat. Mach. Intell., 2020)

Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports. - Keno K. Bressem; Lisa C. Adams; Robert A. Gaudin; Daniel Tröltzsch; Bernd Hamm; Marcus R. Makowski; Chan-Yong Schüle; Janis Lucas Vahldiek; Stefan Markus Niehues (Bioinform., 2021)

3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware. - Keno K. Bressem; Stefan Markus Niehues; Bernd Hamm; Marcus R. Makowski; Janis Lucas Vahldiek; Lisa C. Adams (CoRR, 2021)

Differentially private federated deep learning for multi-site medical image segmentation. - Alexander Ziller; Dmitrii Usynin; Nicolas Remerscheid; Moritz Knolle; Marcus R. Makowski; Rickmer Braren; Daniel Rueckert; Georgios Kaissis (CoRR, 2021)

Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. - Alexander Ziller; Dmitrii Usynin; Moritz Knolle; Kritika Prakash; Andrew Trask; Rickmer Braren; Marcus R. Makowski; Daniel Rueckert; Georgios Kaissis (CoRR, 2021)

Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty. - Moritz Knolle; Alexander Ziller; Dmitrii Usynin; Rickmer Braren; Marcus R. Makowski; Daniel Rueckert; Georgios Kaissis (CoRR, 2021)

U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome Prediction. - Matthias Keicher; Hendrik Burwinkel; David Bani-Harouni; Magdalini Paschali; Tobias Czempiel; Egon Burian; Marcus R. Makowski; Rickmer Braren; Nassir Navab; Thomas Wendler 001 (CoRR, 2021)

Tracked 3D Ultrasound and Deep Neural Network-based Thyroid Segmentation reduce Interobserver Variability in Thyroid Volumetry. - Markus Krönke; Christine Eilers; Desislava Dimova; Melanie Köhler; Gabriel Buschner; Lilit Mirzojan; Lemonia Konstantinidou; Marcus R. Makowski; James Nagarajah; Nassir Navab; Wolfgang Weber 005; Thomas Wendler 001 (CoRR, 2021)

Per-Pixel Lung Thickness and Lung Capacity Estimation on Chest X-Rays using Convolutional Neural Networks. - Manuel Schultheiss; Philipp Schmette; Thorsten Sellerer; Rafael Schick; Kirsten Alexandra Taphorn; Korbinian Mechlem; Lorenz Birnbacher; Bernhard Renger; Marcus R. Makowski; Franz Pfeiffer; Daniela Pfeiffer (CoRR, 2021)

End-to-end privacy preserving deep learning on multi-institutional medical imaging. - Georgios Kaissis; Alexander Ziller; Jonathan Passerat-Palmbach; Théo Ryffel; Dmitrii Usynin; Andrew Trask; Ionésio Lima; Jason Mancuso; Friederike Jungmann; Marc-Matthias Steinborn; Andreas Saleh; Marcus R. Makowski; et al. (Nat. Mach. Intell., 2021)

Adversarial interference and its mitigations in privacy-preserving collaborative machine learning. - Dmitrii Usynin; Alexander Ziller; Marcus R. Makowski; Rickmer Braren; Daniel Rueckert; Ben Glocker; Georgios Kaissis; Jonathan Passerat-Palmbach (Nat. Mach. Intell., 2021)

Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. - Qi Dou 001; Tiffany Y. So; Meirui Jiang; Quande Liu; Varut Vardhanabhuti; Georgios Kaissis; Zeju Li; Weixin Si; Heather H. C. Lee; Kevin Yu; Zuxin Feng; Li Dong; et al. (npj Digit. Medicine, 2021)

Longitudinal Analysis of Disease Progression Using Image and Laboratory Data for Covid-19 Patients. - Francesca De Benetti; Verena Bentele; Egon Burian; Marcus R. Makowski; Nassir Navab; Rickmer Braren; Thomas Wendler 001 (Bildverarbeitung für die Medizin, 2022)

Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection. - Lisa C. Adams; Marcus R. Makowski; Günther Engel; Maximilian Rattunde; Felix Busch; Patrick Asbach; Stefan Markus Niehues; Shankeeth Vinayahalingam; Bram van Ginneken; Geert Litjens 001; Keno K. Bressem (Comput. Biol. Medicine, 2022)

Longitudinal Self-Supervision for COVID-19 Pathology Quantification. - Tobias Czempiel; Coco Rogers; Matthias Keicher; Magdalini Paschali; Rickmer Braren; Egon Burian; Marcus R. Makowski; Nassir Navab; Thomas Wendler 001; Seong Tae Kim 001 (CoRR, 2022)

What Does DALL-E 2 Know About Radiology? - Lisa C. Adams; Felix Busch; Daniel Truhn; Marcus R. Makowski; Hugo J. W. L. Aerts; Keno K. Bressem (CoRR, 2022)

Iodine Images in Dual-energy CT: Detection of Hepatic Steatosis by Quantitative Iodine Concentration Values. - Stefanie Beck; Laurenz Jahn; Dominik Deniffel; Isabelle Riederer; Andreas Sauter; Marcus R. Makowski; Daniela Pfeiffer (J. Digit. Imaging, 2022)

Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. - Qi Dou 001; Tiffany Y. So; Meirui Jiang; Quande Liu; Varut Vardhanabhuti; Georgios Kaissis; Zeju Li; Weixin Si; Heather H. C. Lee; Kevin Yu; Zuxin Feng; Li Dong; et al. (npj Digit. Medicine, 2022)

Hierarchical Multi-Resolution Graph-Cuts for Water-Fat-Silicone Separation in Breast MRI. - Jonathan K. Stelter; Christof Boehm; Stefan Ruschke; Kilian Weiss; Maximilian N. Diefenbach; Mingming Wu; Tabea Borde; Georg P. Schmidt; Marcus R. Makowski; Eva M. Fallenberg; Dimitrios C. Karampinos (IEEE Trans. Medical Imaging, 2022)

Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans. - Michelle Xiao-Lin Foo; Seong Tae Kim 001; Magdalini Paschali; Leili Goli; Egon Burian; Marcus R. Makowski; Rickmer Braren; Nassir Navab; Thomas Wendler 001 (IEEE Access, 2023)

Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. - Soroosh Tayebi Arasteh; Alexander Ziller; Christiane Kuhl; Marcus R. Makowski; Sven Nebelung; Rickmer Braren; Daniel Rueckert; Daniel Truhn; Georgios Kaissis (CoRR, 2023)

Evaluation of GPT-4 for chest X-ray impression generation: A reader study on performance and perception. - Sebastian Ziegelmayer; Alexander W. Marka; Nicolas Lenhart; Nadja Nehls; Stefan Reischl; Felix Harder; Andreas Sauter; Marcus R. Makowski; Markus Graf; Joshua F. Gawlitza (CoRR, 2023)

From Text to Image: Exploring GPT-4Vision's Potential in Advanced Radiological Analysis across Subspecialties. - Felix Busch; Tianyu Han; Marcus R. Makowski; Daniel Truhn; Keno K. Bressem; Lisa Adams (CoRR, 2023)

Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs. - Felix Busch; Lina Xu; Dmitry Sushko; Matthias Weidlich 002; Daniel Truhn; Gustav Müller-Franzes; Maurice M. Heimer; Stefan Markus Niehues; Marcus R. Makowski; Markus Hinsche; Janis Lucas Vahldiek; Hugo J. W. L. Aerts; et al. (Comput. Methods Programs Biomed., 2023)

Unifying Local and Global Shape Descriptors to Grade Soft-Tissue Sarcomas Using Graph Convolutional Networks. - Johannes Kiechle; Stefan M. Fischer; Daniel M. Lang 003; Maxime Di Folco; Sarah C. Foreman; Verena K. N. Rösner; Ann-Kathrin Lohse; Carolin Mogler; Carolin Knebel; Marcus R. Makowski; Klaus Woertler; Stephanie E. Combs; et al. (ISBI, 2024)

Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection. - Felix J. Dorfner; Janis Lucas Vahldiek; Leonhard Donle; Andrei Zhukov; Lina Xu; Hartmut Häntze; Marcus R. Makowski; Hugo J. W. L. Aerts; Fabian Proft; Valeria Rios Rodriguez; Judith Rademacher; Mikhail Protopopov; et al. (CoRR, 2024)

Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data. - Felix J. Dorfner; Amin Dada; Felix Busch; Marcus R. Makowski; Tianyu Han; Daniel Truhn; Jens Kleesiek; Madhumita Sushil; Jacqueline Lammert; Lisa C. Adams; Keno K. Bressem (CoRR, 2024)

Autonomous medical evaluation for guideline adherence of large language models. - Dennis Fast; Lisa C. Adams; Felix Busch; Conor Fallon; Marc Huppertz; Robert Siepmann; Philipp Prucker; Nadine Bayerl; Daniel Truhn; Marcus R. Makowski; Alexander Löser; Keno K. Bressem (npj Digit. Medicine, 2024)

medBERT.de: A comprehensive German BERT model for the medical domain. - Keno K. Bressem; Jens-Michalis Papaioannou; Paul Grundmann; Florian Borchert; Lisa C. Adams; Leonhard Liu; Felix Busch; Lina Xu; Jan P. Loyen; Stefan Markus Niehues; Moritz Augustin; Lennart Grosser; et al. (Expert Syst. Appl., 2024)

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks. - Felix J. Dorfner; Amin Dada; Felix Busch; Marcus R. Makowski; Tianyu Han; Daniel Truhn; Jens Kleesiek; Madhumita Sushil; Lisa C. Adams; Keno K. Bressem (J. Am. Medical Informatics Assoc., 2025)

Parametric shape models for vessels learned from segmentations via differentiable voxelization. - Alina F. Dima; Suprosanna Shit; Huaqi Qiu; Robbie Holland; Tamara T. Mueller; Fabio Musio; Kaiyuan Yang 003; Bjoern H. Menze; Rickmer Braren; Marcus R. Makowski; Daniel Rueckert (CoRR, 2025)

PARROT: An Open Multilingual Radiology Reports Dataset. - Bastien Le Guellec; Kokou Adambounou; Lisa C. Adams; Thibault Agripnidis; Sungsoo Ahn; Radhia Ait Chalal; Tugba Akinci D. Antonoli; Philippe Amouyel; Henrik Andersson; Raphael Bentegeac; Claudio Benzoni; Antonino Andrea Blandino; et al. (CoRR, 2025)