A Method for Semantic Knee Bone and Cartilage Segmentation with Deep 3D Shape Fitting Using Data from the Osteoarthritis Initiative. - Justus Schock; Marcin Kopaczka; Benjamin Agthe; Jie Huang; Paul Kruse; Daniel Truhn; Stefan Conrad 001; Gerald Antoch; Christiane Kuhl; Sven Nebelung; Dorit Merhof (ShapeMI@MICCAI, 2020)

Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. - Tianyu Han; Sven Nebelung; Federico Pedersoli; Markus Zimmermann; Maximilian Schulze-Hagen; Michael Ho; Christoph Haarburger; Fabian Kiessling; Christiane Kuhl; Volkmar Schulz; Daniel Truhn (CoRR, 2020)

A Novel Combined Level Set Model for Carpus Segmentation from Magnetic Resonance Images with Prior Knowledge aligned in Polar Coordinate System. - Jianzhang Li; Sven Nebelung; Justus Schock; Björn Rath; Markus Tingart; Yu Liu; Nad Siroros; Jörg Eschweiler (Comput. Methods Programs Biomed., 2021)

Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. - Tianyu Han; Jakob Nikolas Kather; Federico Pedersoli; Markus Zimmermann; Sebastian Keil; Maximilian Schulze-Hagen; Marc Terwoelbeck; Peter Isfort; Christoph Haarburger; Fabian Kiessling; Volkmar Schulz; Christiane Kuhl; et al. (CoRR, 2021)

Monoplanar CT Reconstruction with GANs. - Justus Schock; Yu-Chia Lan; Daniel Truhn; Marcin Kopaczka; Stefan Conrad 001; Sven Nebelung; Dorit Merhof (IPTA, 2022)

Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation. - Firas Khader; Gustav Mueller-Franzes; Soroosh Tayebi Arasteh; Tianyu Han; Christoph Haarburger; Maximilian Schulze-Hagen; Philipp Schad; Sandy Engelhardt; Bettina Baeßler; Sebastian Foersch; Johannes Stegmaier; Christiane Kuhl; et al. (CoRR, 2022)

Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels. - Soroosh Tayebi Arasteh; Peter Isfort; Marwin Saehn; Gustav Mueller-Franzes; Firas Khader; Jakob Nikolas Kather; Christiane Kuhl; Sven Nebelung; Daniel Truhn (CoRR, 2022)

Diffusion Probabilistic Models beat GANs on Medical Images. - Gustav Müller-Franzes; Jan Moritz Niehues; Firas Khader; Soroosh Tayebi Arasteh; Christoph Haarburger; Christiane Kuhl; Tianci Wang; Tianyu Han; Sven Nebelung; Jakob Nikolas Kather; Daniel Truhn (CoRR, 2022)

Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis. - Firas Khader; Gustav Mueller-Franzes; Tianci Wang; Tianyu Han; Soroosh Tayebi Arasteh; Christoph Haarburger; Johannes Stegmaier; Keno K. Bressem; Christiane Kuhl; Sven Nebelung; Jakob Nikolas Kather; Daniel Truhn (CoRR, 2022)

Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. - Tianyu Han; Jakob Nikolas Kather; Federico Pedersoli; Markus Zimmermann; Sebastian Keil; Maximilian Schulze-Hagen; Marc Terwoelbeck; Peter Isfort; Christoph Haarburger; Fabian Kiessling; Christiane Kuhl; Volkmar Schulz; et al. (Nat. Mac. Intell., 2022)

Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection. - Firas Khader; Gustav Müller-Franzes; Soroosh Tayebi Arasteh; Tianyu Han; Jakob Nikolas Kather; Johannes Stegmaier; Sven Nebelung; Daniel Truhn (ISBI, 2023)

Multi-View Abnormality Detection in Clinical Knee MRI Studies Using Transformers. - Firas Khader; Johannes Stegmaier; Sven Nebelung; Daniel Truhn (ISBI, 2023)

Transformers for CT Reconstruction from Monoplanar and Biplanar Radiographs. - Firas Khader; Gustav Müller-Franzes; Tianyu Han; Sven Nebelung; Christiane Kuhl; Johannes Stegmaier; Daniel Truhn (SASHIMI@MICCAI, 2023)

Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. - Firas Khader; Jakob Nikolas Kather; Tianyu Han; Sven Nebelung; Christiane Kuhl; Johannes Stegmaier; Daniel Truhn (MLMI@MICCAI (2), 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)

Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation. - Gustav Müller-Franzes; Fritz Müller-Franzes; Luisa Huck; Vanessa Raaff; Eva Kemmer; Firas Khader; Soroosh Tayebi Arasteh; Teresa Nolte; Jakob Nikolas Kather; Sven Nebelung; Christiane Kuhl; Daniel Truhn (CoRR, 2023)

Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy. - Soroosh Tayebi Arasteh; Mahshad Lotfinia; Teresa Nolte; Marwin Saehn; Peter Isfort; Christiane Kuhl; Sven Nebelung; Georgios Kaissis; Daniel Truhn (CoRR, 2023)

Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images. - Soroosh Tayebi Arasteh; Leo Misera; Jakob Nikolas Kather; Daniel Truhn; Sven Nebelung (CoRR, 2023)

Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies. - Soroosh Tayebi Arasteh; Tianyu Han; Mahshad Lotfinia; Christiane Kuhl; Jakob Nikolas Kather; Daniel Truhn; Sven Nebelung (CoRR, 2023)

Medical Foundation Models are Susceptible to Targeted Misinformation Attacks. - Tianyu Han; Sven Nebelung; Firas Khader; Tianci Wang; Gustav Mueller-Franzes; Christiane Kuhl; Sebastian Försch; Jens Kleesiek; Christoph Haarburger; Keno K. Bressem; Jakob Nikolas Kather; Daniel Truhn (CoRR, 2023)

Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining. - Tianyu Han; Laura Zigutyte; Luisa Huck; Marc Huppertz; Robert Siepmann; Yossi Gandelsman; Christian Blüthgen; Firas Khader; Christiane Kuhl; Sven Nebelung; Jakob Nikolas Kather; Daniel Truhn (CoRR, 2023)

Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models. - Soroosh Tayebi Arasteh; Christiane Kuhl; Marwin-Jonathan Saehn; Peter Isfort; Daniel Truhn; Sven Nebelung (CoRR, 2023)

On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. - Tianyu Han; Sven Nebelung; Firas Khader; Jakob Nikolas Kather; Daniel Truhn (MICCAI (7), 2024)

An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs. - Patrick Wienholt; Alexander Hermans; Firas Khader; Behrus Puladi; Bastian Leibe; Christiane Kuhl; Sven Nebelung; Daniel Truhn (CoRR, 2024)

Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization. - Firas Khader; Omar S. M. El Nahhas; Tianyu Han; Gustav Müller-Franzes; Sven Nebelung; Jakob Nikolas Kather; Daniel Truhn (CoRR, 2024)

RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation. - Soroosh Tayebi Arasteh; Mahshad Lotfinia; Keno K. Bressem; Robert Siepmann; Dyke Ferber; Christiane Kuhl; Jakob Nikolas Kather; Sven Nebelung; Daniel Truhn (CoRR, 2024)

Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2. - Gustav Müller-Franzes; Firas Khader; Robert Siepmann; Tianyu Han; Jakob Nikolas Kather; Sven Nebelung; Daniel Truhn (CoRR, 2024)

Medical large language models are susceptible to targeted misinformation attacks. - Tianyu Han; Sven Nebelung; Firas Khader; Tianci Wang; Gustav Müller-Franzes; Christiane Kuhl; Sebastian Försch; Jens Kleesiek; Christoph Haarburger; Keno K. Bressem; Jakob Nikolas Kather; Daniel Truhn (npj Digit. Medicine, 2024)

Encrypted federated learning for secure decentralized collaboration in cancer image analysis. - Daniel Truhn; Soroosh Tayebi Arasteh; Oliver Lester Saldanha; Gustav Müller-Franzes; Firas Khader; Philip Quirke; Nicholas P. West; Richard Gray 005; Gordon G. A. Hutchins; Jacqueline A. James; Maurice B. Loughrey; Manuel Salto-Tellez; et al. (Medical Image Anal., 2024)

Three-dimensional end-to-end deep learning for brain MRI analysis. - Radhika Juglan; Marta Ligero; Zunamys I. Carrero; Asier Rabasco Meneghetti; Tim Lenz; Leo Misera; Gregory Patrick Veldhuizen; Paul Kuntke; Hagen H. Kitzler; Sven Nebelung; Daniel Truhn; Jakob Nikolas Kather (CoRR, 2025)