Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis. - Petra Welter; Jörg Riesmeier; Benedikt Fischer; Christoph Grouls; Christiane Kuhl; Thomas Martin Deserno (J. Am. Medical Informatics Assoc., 2011)

IRMA Code II - A New Concept for Classification of Medical Images. - Tim-Christian Piesch; Henning Müller; Christiane Kuhl; Thomas Martin Deserno (Bildverarbeitung für die Medizin, 2012)

IRMA Code II: Unique Annotation of Medical Images for Access and Retrieval. - Tim-Christian Piesch; Henning Müller; Christiane Kuhl; Thomas Martin Deserno (MIE, 2012)

Black Box Integration of Computer-Aided Diagnosis into PACS Deserves a Second Chance: Results of a Usability Study Concerning Bone Age Assessment. - Ina Geldermann; Christoph Grouls; Christiane Kuhl; Thomas Martin Deserno; Cord Spreckelsen (J. Digit. Imaging, 2013)

Influence of trigger type, tube voltage and heart rate on calcified plaque imaging in dual source cardiac computed tomography: phantom study. - Tobias Penzkofer; Eva Donandt; Peter Isfort; Thomas Allmendinger; Christiane K. Kuhl; Andreas H. Mahnken; Philipp Bruners (BMC Medical Imaging, 2014)

A miniature accelerometer-based guidance device for percutaneous computed tomography-guided punctures. - Christoph Wilkmann; Nobutake Ito; Tobias Penzkofer; Peter Isfort; Hong-Sik Na; Michael Hennes; Catherine Disselhorst-Klug; Andreas H. Mahnken; Christiane K. Kuhl; Philipp Bruners (Int. J. Comput. Assist. Radiol. Surg., 2015)

Transfer Learning for Breast Cancer Malignancy Classification based on Dynamic Contrast-Enhanced MR Images. - Christoph Haarburger; Peter Langenberg; Daniel Truhn; Hannah Schneider; Johannes Thüring; Simone Schrading; Christiane K. Kuhl; Dorit Merhof (Bildverarbeitung für die Medizin, 2018)

Abbreviated breast biopsy procedure by registration of craniocaudal and mediolateral breast MR images. - Christoph Haarburger; Johannes Ruther; Daniel Truhn; Simone Schrading; Daniel Bug; Christiane K. Kuhl; Dorit Merhof (ISBI, 2018)

Prediction of Liver Function Based on DCE-CT. - Oliver Rippel; Daniel Truhn; Johannes Thüring; Christoph Haarburger; Christiane K. Kuhl; Dorit Merhof (Bildverarbeitung für die Medizin, 2019)

Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification. - Christoph Haarburger; Michael Baumgartner 001; Daniel Truhn; Mirjam Broeckmann; Hannah Schneider; Simone Schrading; Christiane Kuhl; Dorit Merhof (MICCAI (4), 2019)

Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks. - Christoph Haarburger; Nicolas Horst; Daniel Truhn; Mirjam Broeckmann; Simone Schrading; Christiane Kuhl; Dorit Merhof (VCBM, 2019)

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)

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)

Automated major psoas muscle volumetry in computed tomography using machine learning algorithms. - Felix Duong; Michael Gadermayr; Dorit Merhof; Christiane Kuhl; Philipp Bruners; Sven H. Loosen; Christoph Roderburg; Daniel Truhn; Maximilian F. Schulze-Hagen (Int. J. Comput. Assist. Radiol. Surg., 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)

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)

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)

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)

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 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)