Radiomic Feature Stability Analysis Based on Probabilistic Segmentations. - Christoph Haarburger; Justus Schock; Daniel Truhn; Philippe Weitz; Gustav Mueller-Franzes; Leon Weninger; Dorit Merhof (ISBI, 2020)

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)

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)

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)

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)

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)

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)

Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance. - Jan Moritz Niehues; Gustav Müller-Franzes; Yoni Schirris; Sophia J. Wagner; Michael Jendrusch; Matthias Kloor; Alexander T. Pearson; Hannah Sophie Muti; Katherine Jane Hewitt; Gregory Patrick Veldhuizen; Laura Zigutyte; Daniel Truhn; et al. (Comput. Biol. Medicine, 2024)

In-context learning enables multimodal large language models to classify cancer pathology images. - Dyke Ferber; Georg Wölflein; Isabella C. Wiest; Marta Ligero; Srividhya Sainath; Narmin Ghaffari Laleh; Omar S. M. El Nahhas; Gustav Müller-Franzes; Dirk Jäger; Daniel Truhn; Jakob Nikolas Kather (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)

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)

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report. - Evi M. C. Huijben; Maarten L. Terpstra; Arthur Jr Galapon; Suraj Pai; Adrian Thummerer; Peter Koopmans; Manya Afonso; Maureen A. J. M. van Eijnatten; Oliver J. Gurney-Champion; Zeli Chen; Yiwen Zhang; Kaiyi Zheng; et al. (Medical Image Anal., 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)

A European Multi-Center Breast Cancer MRI Dataset. - Gustav Müller-Franzes; Lorena Escudero Sanchez; Nicholas Payne; Alexandra Athanasiou; Michael Kalogeropoulos; Aitor Lopez; Alfredo Miguel Soro Busto; Julia Camps Herrero; Nika Rasoolzadeh; Tianyu Zhang 006; Ritse Mann; Debora Jutz; et al. (CoRR, 2025)