Lab for Artificial Intelligence in Medicine
We are a young, diverse, and interdisciplinary team of scientists dedicated to developing deep learning methods for medical applications. Our goal is to extract valuable knowledge from clinical routine data and advance diagnostics and treatment in precision medicine.
We focus on developing and applying advanced machine learning techniques to extract actionable insights from clinical routine data.
Affiliations
We are based at the Department of Diagnostic and Interventional Radiology of Uniklinik RWTH Aachen (Germany) in close proximity to neighbouring Belgium and the Netherlands.
Funding
We are currently funded by the German Research Foundation (DFG) (MAMMA - 515639690, Detection of Early Osteoarthritis - 417508432, Computational Biomechanics -517243167), the Federal Ministry of Research, Technology and Space (Transform Liver - 031L0312C, DECIPHER-M, 01KD2420B), the European Union (Horizon Europe: ODELIA - GA 101057091, JAIF – 101250682 and ERC Starting Grant SAGMA – GA 101222556 ) and the ERDF NRW (Kimona - 20801783).
Contact
Univ.-Prof. Dr. med. Dipl.-Phys. Daniel Truhn, M.Sc., Group leader
Priv.-Doz. Dr. med. Sven Nebelung, Senior scientist
Dr. Juliana de Castilhos, Scientific Coordinator
Vera Winter, Research coordinator
AImedicineukaachende
Research
We develop multimodal fusion algorithms that combine information from multiple imaging modalities, patient histories, and multi-omics data. By integrating these diverse data sources, we aim to enable more precise diagnostic, prognostic, and therapeutic decisions.
We investigate the potential of generative models, such as diffusion models and Generative Adversarial Networks (GANs), in the medical domain. We leverage these techniques to synthesize realistic medical images for data sharing or augmentation of training data. By pushing the boundaries of generative modeling, we seek to enhance the capabilities of AI systems in healthcare.
We explore the capabilities of large language models in processing and analyzing medical data. By fine-tuning these models on domain-specific medical texts and electronic health records, we aim to extract valuable insights, generate clinical summaries, and support decision-making processes. Our research investigates the potential of language models in tasks such as medical question answering, clinical note summarization, and patient risk stratification.
One of our primary areas of expertise is precision oncology of solid tumors, including immunotherapy. We develop deep learning methods for automated tumor segmentation, characterization, and treatment response assessment from medical images. Our research aims to reduce inter-observer variability in cancer diagnosis and provide objective tools to assist pathologists and radiologists. We also work on identifying clinically relevant morphologic phenotypes and biomarkers associated with response to specific therapeutic agents.
Our lab also focuses on applying AI techniques to musculoskeletal imaging. We develop methods for automated segmentation and analysis of musculoskeletal structures, such as bones, cartilage, and tendons, from MRI data. Our research aims to improve the accuracy and efficiency of musculoskeletal disease diagnosis, monitor disease progression, and assess treatment outcomes. We collaborate closely with clinical experts to develop AI-aided diagnostic tools that can be integrated into clinical workflows.
Team
Lab Leadership
Daniel is a physicist, imaging scientist, and clinical radiologist with a dedicated focus on machine learning and magnetic resonance imaging. After studying physics at RWTH Aachen University and Imperial College in London, he continued to satisfy his thirst for knowledge by studying medicine at RWTH Aachen University. In 2013, he completed his MD thesis on the compatibility of positron emission tomography and magnetic resonance imaging and joined the Department of Diagnostic and Interventional Radiology (University Hospital Aachen) to become a board-certified clinical radiologist in 2019. Besides his clinical work, he pursued his research interests in machine learning as a fellow at the Institute of Imaging and Computer Vision (RWTH Aachen University) for two years before returning to the clinic where he currently leads the interdisciplinary research group “AI in Medical Imaging”. His research focuses on bringing machine learning-methods into clinical practice and on bridging the gaps between research possibilities and clinical applicability. His recent publications are listed on Google Scholar and Pubmed.
Senior Scientist
Sven is a clinical radiologist and imaging scientist focusing on clinically motivated imaging research that aims to refine image acquisition and post-processing methodologies in close collaboration with clinicians, clinical scientists, engineers, physicists, and imaging scientists. After studying medicine at RWTH Aachen University, he completed his MD thesis on cartilage tissue engineering. He joined the Department of Orthopedics (University Hospital Aachen) to receive orthopedic training during the surgical common trunk. After undertaking research at the Institute of Anatomy (RWTH Aachen University) in 2015, he entered Radiology specialist training at the Department of Diagnostic and Interventional Radiology (University Hospital Aachen). After completing a research stay at the Department of Diagnostic and Interventional Radiology (University Hospital Düsseldorf) from 2019 to 2021, he moved back to Aachen to lead the group. In 2022, he was board-certified as a radiologist and has been working as an attending physician I the Department of Diagnostic and Interventional Radiology (University Hospital Aachen) ever since, focusing his clinical work on MRI and musculoskeletal pathologies. His research is generously funded by the German Research Association (DFG) and funds from RWTH Aachen University. His recent publications are listed on Google Scholar and Pubmed. He also regularly reviews manuscripts for medical, technical, and interdisciplinary scientific journals.
Research Coordinator & IT Systems Administrator
Vera joined the team in January 2024 as research coordinator. She has a vast experience in the field of research funding and project management and is passionate about supporting researchers so they can focus on the science. Before joining our team she was in charge of EU funded research projects, in particular European Research Council (ERC), at RWTH Aachen University and worked in project and stakeholder management at the European Spallation Source in Lund, Sweden. Vera has studied European Studies, International Relations and Research Management in Maastricht, Braga, Malmö and Speyer.
Juliana joined the Lab for AI in Medicine at University Hospital RWTH Aachen as Scientific Coordinator in January 2026. She works across research projects and workflows, with a strong focus on scientific communication, publication support, and cross-project coordination. Prior to joining the lab, she held academic faculty positions abroad and later worked at the M3 Research Center (Malignome, Metabolome and Microbiome), University Hospital Tübingen, as a senior postdoctoral researcher in translational microbiome research. Her scientific background includes microbiome research and interdisciplinary biomedical science, with experience in cancer biology.
Jan is a dedicated System Administrator with a passion for technology. Joining the group on June 20, 2024, he brings valuable skills and knowledge acquired through his training as an IT specialist in system integration at RWTH Aachen University. Jan is committed to ensuring smooth system operations and providing excellent technical support.
PhD Students
Paul is a PhD student (Dr. rer. medic.) at Uniklinik RWTH Aachen, specializing in computer vision and the integration of Large Language Models (LLMs) and AI agents into software systems. He holds a Master's degree in Computer Science from RWTH Aachen University and a Bachelor's degree in Computer Visualization from Otto-von-Guericke-Universität Magdeburg. Paul began his master's thesis in the research group in November 2024 and joined as a doctoral researcher in August 2025
Marvin received both his B.Sc. and M.Sc. in Computer Science from RWTH University. He specialized in IT security and explored the intersection of machine learning and network security in his master’s thesis. He joined the Machine Learning and Musculoskeletal Imaging group as a research scientist in 2024, allowing him to combine his passion for computer science with his curiosity for medicine. His current focus is on investigating the potential of advanced models, such as LVMs, in the medical field, with the aim of bringing new insights and innovations to medical imaging and diagnostics.
Kilian received his M.Sc. in Computer Science from RWTH Aachen University and his B.Sc. in Computer Engineering from Otto-von-Guericke University Magdeburg. During his studies, he specialized in deep learning and anomaly detection, completing his master's thesis on utilizing temporal dependencies for intrusion detection. He gained practical experience during his studies in applied machine learning at Fraunhofer IPT and Porsche AG. Now as a PhD student, Kilian aims to apply advanced machine learning techniques and state-of-the-art LLMs to the medical field. He is particularly interested in enhancing medical applications to bridge the gap between theoretical AI models and clinical implementation.
Eneko studied medicine at Universidad de Navarra in Pamplona, Spain. He joined the team in August 2024 and is currently working on his Dr. med. degree. During his bachelor’s studies, he investigated the radiomic features of otosclerosis, which fuelled his interest in radiology, and especially its intersection with technology. Currently, Eneko is focusing on both computer vision and natural language processing projects. His goal is to develop models that have a significant clinical impact, bridging the gap between advanced technology and practical medical applications.
Roman is a passionate PhD Student (Dr. rer. medic) blending his academic foundation in computer science with a keen interest in medical AI. Having completed both his master's and bachelor's degrees at RWTHS Aachen, he has experience in machine learning, data science, and high-performance computing. His academic journey has been driven by a fascination with expanding the problem-solving capabilities of artificial computational systems and extracting valuable insights from challenging datasets. Presently, he collaborates closely with medical experts, leveraging established deep-learning techniques to unlock new clinical insights while conducting research into novel deep-learning methods for the medical domain.
Patrick is a PhD (Dr. rer. medic.) candidate and researcher. He has studied computer science and received his bachelor's and master's degrees from RWTH Aachen University. During his studies, he focused on machine learning with a special emphasis on computer vision. Since the beginning he took lectures with a focus on medicine and medical engineering. In his research, he uses his expertise to push medical deep learning research beyond the current state of the art.
Hanna completed her Bachelor’s in Biotechnology at RWTH and wrote her thesis on pharmacokinetical modeling. She then decided to combine her interest in medicine and technology by switching to Biomedical Engineering for her master’s. During a research internship on MRI image reconstruction at the Montreal Neurological Institute, she discovered her love for medical imaging and everything data-related. Therefore, she further explored the field afterwards by writing her master’s thesis at Forschungszentrum Jülich on the topic of fMRI and qMRI image analysis. Now, she’s excited to keep learning about AI and how it can be leveraged in the clinical context.
Mahta is a doctoral student at Uniklinik RWTH Aachen, delving into Machine Learning and Musculoskeletal Imaging since January 2024. She's on a mission to create user-friendly interfaces for medical experts, integrating AI models seamlessly while keeping them explainable in medical contexts. Leveraging open source platforms, she's optimizing user interaction for efficient AI integration into clinical practice. Before her doctoral studies, Mahta earned an M.Sc. in Software Systems Engineering from RWTH Aachen and a B.Sc. in Computer Engineering from Tehran, Iran. With industrial experience in backend and frontend development, she's worked on various projects, including financial data services and banking web apps. Mahta's research interests range from software engineering for machine learning to user interface design in medical imaging platforms and MLOps. Outside work, she enjoys fitness, painting, travel, and continuous learning.
Debora is a medical computer scientist focusing on machine learning classifying breast magnetic resonance images. She studied medical computer science at University Heidelberg and Heilbronn University for the bachelors degree. She continued her academic journey in Tübingen where she worked as a research assistant in 2022, focusing on privacy-preserving machine learning techniques. This role allowed her to deepen her expertise in safeguarding sensitive data during model training and inference. Debora completed her M.Sc. in medical computer science from the University of Tübingen in 2023, specializing in security. Her master's thesis focused on implementing inference on a privacy-preserving Convolutional Neural Network (CNN) using secure three-party computation.
Simon studied Computational Social Systems at RWTH Aachen for his Master's degree and joined the group in 2021 as a student researcher. After completing his studies, he became a full-time PhD student and research fellow in 2023. His work is focused on developing novel methods for anatomical landmark detection in 3D magnetic resonance imaging and building AI-aided diagnostic tools for clinical practice.
Zihao joined the team as a PhD candidate in November 2025, with a really interdisciplinary background. He initially enrolled in Civil Engineering during his Bachelor’s studies, but later gave up and transferred to Remote Sensing. After graduation, he transferred once again to Computer Science and conducted several research projects on computer-aided diagnosis models. Currently, Zihao is working on foundation model–driven agent systems, with the goal of advancing the explainability and transparency of next-generation computer-aided diagnosis tools. See more in Google Scholar.
Daniel Geiger holds a B.Sc. and M.Sc. in Electrical Engineering from RWTH Aachen University, both specialized in Biomedical Systems Engineering. His expertise ranges from medical hardware development—including medical information systems and signal processing of vital signs at MedIT—to advanced image processing for OCT and microscopy cell analysis at Fraunhofer IPT and the Chair of Imaging and Computer Vision. Currently, his research focuses on designing network architectures for medical computer vision and developing agentic multimodal reasoning models to improve interpretable diagnostic decision-making. Combining a strong engineering background with innovative AI methods, Daniel aims to create transparent and intelligent systems that support and enhance medical diagnostics.
Frederik is a medical doctor and physicist from Heinrich-Heine-University Düsseldorf. In his research, he develops explainable AI methods, network architectures, and agentic reasoning systems for medical applications. His work aims to make AI decision-making in healthcare more transparent and interpretable while creating systems that can reason through complex clinical scenarios. Leveraging his unique background bridging medicine, physics, and machine learning, he strives to advance trustworthy and intelligent AI that can assist healthcare professionals in delivering better patient care.
Postdoctoral Researchers
Dennis Eschweiler is a research scientist at the Machine Learning and Musculoskeletal Imaging group at the RWTH University Hospital. He received bachelor's and master's degrees in electrical engineering from RWTH Aachen University in 2015 and 2018, respectively. During his PhD at the Institute of Imaging and Computer Vision at RWTH Aachen University, he worked on deep learning-based approaches for segmentation and generative models for 3D biomedical image data. He joined the group in 2024 and is involved in various projects with the primary goal of bringing deep learning-based approaches into clinical practice.
Soroosh is an AI scientist and electrical & computer engineer. He completed his M.Sc. in signal processing and communications engineering at the University of Erlangen-Nuremberg (FAU). Keen to delve deeper into research and innovation, Soroosh embarked on his master's thesis at Harvard Medical School. He joined the group in 02/2022 for a PhD in AI in Medical Image Processing from RWTH Aachen University. Currently, he is a postdoctoral researcher at the group, working on multiple projects such as privacy-preserving medical deep learning, generative AI, and multimodal AI. For a more detailed insight, visit his personal website Here.
Tianyu Han
Alexander Hermans
Firas Khader
Gustav Müller-Franzes
Publications
Mohammadi M, Vejdanihemmat M, Lotfinia M, Rusu M, Truhn D, Maier A, Tayebi Arasteh S,
Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications.
In: NPJ Digital Medicine
Baldus SG, Wiesmann M, Habel U, Gerhards A, Hasan D, Weyland CS, Truhn D, Hasl MM, Clemens B, Nikoubashman O,
Patients' views on the use of artificial intelligence in healthcare: Artificial Intelligence Survey Aachen (AISA)-a prospective survey.
In: Insights into Imaging
Misera L, Nebelung S, Carrero ZI, Bressem K, Ligero M, Kühn JP, Hoffmann RT, Truhn D, Kather JN,
Reducing manual workload in CT and MRI annotation with the Segment Anything Model 2.
In: BMC Medical Imaging
Truhn D, Azizi S, Zou J, Cerda-Alberich L, Mahmood F, Kather JN,
Artificial intelligence agents in cancer research and oncology.
In: Nature reviews Cancer
Woźnicki P, Laqua C, Fiku I, Hekalo A, Truhn D, Engelhardt S, Kather J, Foersch S, D’Antonoli TA, Pinto Dos Santos D, Baeßler B, Laqua FC,
Automatic structuring of radiology reports with on-premise open-source large language models.
In: European Radiology
Truhn D, Kather JN.
Synthetic chest X-ray images from text prompts.
In: Nat Biomed Eng
Okolie A, Dirrichs T, Huck LC, Nebelung S, Arasteh ST, Nolte T, Han T, Kuhl CK, Truhn D,
Accelerating breast MRI acquisition with generative AI models.
In: European Radiology
El Nahhas OSM, van Treeck M, Wölflein G, Unger M, Ligero M, Lenz T, Wagner SJ, Hewitt KJ, Khader F, Foersch S, Truhn D, Kather JN,
From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology.
In: Nature Protocols
Huppertz MS, Siepmann R, Topp D, Nikoubashman O, Yüksel C, Kuhl CK, Truhn D, Nebelung S,
Revolution or risk?-Assessing the potential and challenges of GPT-4V in radiologic image interpretation.
In: European Radiology
Busch F, Hoffmann L, Dos Santos DP, Makowski MR, Saba L, Prucker P, Hadamitzky M, Navab N, Kather JN, Truhn D, Cuocolo R, Adams LC, Bressem KK,
Large language models for structured reporting in radiology: past, present, and future.
In: European Radiology
Žigutytė L, Lenz T, Han T, Hewitt KJ, Reitsam NG, Foersch S, Carrero ZI, Unger M, Pearson AT, Truhn D, Kather JN,
Counterfactual Diffusion Models for Interpretable Morphology-based Explanations of Artificial Intelligence Models in Pathology.
In: bioRxiv : the preprint server for biology
Busch F, Hoffmann L, Rueger C, van Dijk EH, Kader R, Ortiz-Prado E, Makowski MR, Saba L, Hadamitzky M, Kather JN, Truhn D, Cuocolo R, Adams LC, Bressem KK,
Current applications and challenges in large language models for patient care: a systematic review.
In: Communications Medicine
Clusmann J, Ferber D, Wiest IC, Schneider CV, Brinker TJ, Foersch S, Truhn D, Kather JN,
Prompt injection attacks on vision language models in oncology.
In: Nature Communications
Saldanha OL, Zhu J, Müller-Franzes G, Carrero ZI, Payne NR, Escudero Sánchez L, Varoutas PC, Kyathanahally S, Laleh NG, Pfeiffer K, Ligero M, Behner J, Abdullah KA, Apostolakos G, Kolofousi C, Kleanthous A, Kalogeropoulos M, Rossi C, Nowakowska S, Athanasiou A, Perez-Lopez R, Mann R, Veldhuis W, Camps J, Schulz V, Wenzel M, Morozov S, Ciritsis A, Kuhl C, Gilbert FJ, Truhn D, Kather JN,
Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging.
In: Communications Medicine
Dorfner FJ, Dada A, Busch F, Makowski MR, Han T, Truhn D, Kleesiek J, Sushil M, Adams LC, Bressem KK,
Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks.
In: Journal of the American Medical Informatics Association: JAMIA
Westfechtel SD, Kußmann K, Aßmann C, Huppertz MS, Siepmann RM, Lemainque T, Winter VR, Barabasch A, Kuhl CK, Truhn D, Nebelung S,
AI in motion: the impact of data augmentation strategies on mitigating MRI motion artifacts.
In: European Radiology
Chen Y, Laevens BPM, Lemainque T, Müller-Franzes GA, Seibel T, Dlugosch C, Clusmann J, Koop PH, Gong R, Liu Y, Jakhar N, Cao F, Schophaus S, Raju TB, Raptis AA, van Haag F, Joy J, Loomba R, Valenti L, Kather JN, Brinker TJ, Herzog M, Costa IG, Hernando D, Schneider KM, Truhn D, Schneider CV,
Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease.
In: Liver international: official journal of the International Association for the Study of the Liver
Ferber D, El Nahhas OSM, Wölflein G, Wiest IC, Clusmann J, Leßmann ME, Foersch S, Lammert J, Tschochohei M, Jäger D, Salto-Tellez M, Schultz N, Truhn D, Kather JN,
Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology.
In: Nature Cancer
Ziegelmayer S, Häntze H, Mertens C, Busch F, Lemke T, Kather JN, Truhn D, Kim SH, Wiestler B, Graf M, Kader A, Bamberg F, Schlett CL, Weiss JB, Schulz-Menger J, Ringhof S, Can E, Pischon T, Niendorf T, Lammert J, Schulze M, Keil T, Peters A, Hadamitzky M, Makowski MR, Adams L, Bressem K,
Intermuscular adipose tissue and lean muscle mass assessed with MRI in people with chronic back pain in Germany: a retrospective observational study.
In: The Lancet Regional Health - Europe
Busch F, Hoffmann L, Xu L, Zhang LJ, Hu B, García-Juárez I, Toapanta-Yanchapaxi LN, Gorelik N, Gorelik V, Rodriguez-Granillo GA, Ferrarotti C, Cuong NN, Thi CAP, Tuncel M, Kaya G, Solis-Barquero SM, Mendez Avila MC, Ivanova NG, Kitamura FC, Hayama KYI, Puntunet Bates ML, Torres PI, Ortiz-Prado E, Izquierdo-Condoy JS, Schwarz GM, Hofstaetter JG, Hide M, Takeda K, Peric B, Pilko G, Thulesius HO, Lindow T, Kolawole IK, Olatoke SA, Grzybowski A, Corlateanu A, Iaconi OS, Li T, Domitrz I, Kepczynska K, Mihalcin M, Fašaneková L, Zatonski T, Fulek K, Molnár A, Maihoub S, da Silva Gama ZA, Saba L, Sountoulides P, Makowski MR, Aerts HJWL, Adams LC, BressemKK, Navarro ÁA, Águas C, Aineseder M, Alomar M, Al Sliman R, Anand G, Angkurawaranon S, Aoki S, Arkoh S, Ashraf G, Astri Y, Bakhshi S, Bayramov NY, Billis A, Bitencourt AGV, Bolejko A, Bollas Becerra AJ, Bwambale J, Capela A, Cau R, Chacon-Acevedo KR, Chaunzwa TL, Chojniak R, Clements W, Cuocolo R, Dahlblom V, Sousa KM, Villarrubia JE, Desai VB, Dhakal AK, Dignum V, Andrade RGF, Ferraioli G, Ganguly S, Garg H, Savevska CG, Radovikj MG, Gkartzoni A, Gorospe L, Griffin I, Hadamitzky M, Ndahiro MH, Hering A, Hochhegger B, Huseynova MR, Ishida F, Jha N, Jiang L, Kader R, Kavnoudias H, Klein C, Kolostoumpis G, Koshy A, Kruger NA, Löser A, Lucijanic M, MantziariD, Margue G, McFadden S, Miyake M, Morakote W, Ngabonziza I, Nguyen TT, Niehues SM, Nortje M, Palaian S, Pentara NV, de Almeida RPP, Poma G, Purwoko M, Pyrgidis N, Rafailidis V, Rainey C, Ribeiro JC, Agudelo NR, Sado K, Saidman JM, Saturno-Hernandez PJ, Suryadevara V, Schulz GB, Soric E, Soto-Pérez-Olivares J, Stanzione A, Struck JP, Takaoka H, Tanioka S, Huyen TTM, Truhn D, van Dijk EHC, van Wijngaarden P, Wang YC, Weidlich M, Zhang S,
Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients.
In: JAMA Network Open
Josephs G, Hitpass L, Truhn D, Meister F, Berres ML, Luedde T, Jonigk D, Olde Damink SWM, Lang SA, Vondran F, Amygdalos I,
Splenic hypertrophy predicts liver-specific complications in patients undergoing major liver resection for colorectal liver metastases, after preoperative chemotherapy.
In: Hepatobiliary Surgery And Nutrition
Tayebi Arasteh S, Lotfinia M, Bressem K, Siepmann R, Adams L, Ferber D, Kuhl C, Kather JN, Nebelung S, Truhn D,
RadioRAG: Online Retrieval-Augmented Generation for Radiology Question Answering.
In: Radiology: Artificial intelligence
Meneghetti AR, Hernández ML, Kühn JP, Löck S, Carrero ZI, Perez-Lopez R, Bressem KK, Brinker TJ, Pearson AT, Truhn D, Nebelung S, Kather JN,
End-to-end prediction of clinical outcomes in head and neck squamous cell carcinoma with foundation model-based multiple instance learning.
In: BMC Artificial intelligence
Marion I, Schulz S, Glasner C, Kather JN, Truhn D, Eckstein M, Mueller C, Fernandez A, Marquard S, Oliver Metzig M, Roth W, Gaida MM, Strobl S, Wagner DC, Schad A, Jesinghaus M, Hartmann N, Musholt TJ, Staubitz-Vernazza JI, Foersch S,
Deep Learning Discovers New Morphological Features while Predicting Genetic Alterations from Histopathology of Papillary Thyroid Carcinoma.
In: Thyroid: official journal of the American Thyroid Association
Müller-Franzes G, Khader F, Siepmann R, Han T, Kather JN, Nebelung S, Truhn D,
Medical slice transformer for improved diagnosis and explainability on 3D medical images with DINOv2.
In: Scientific Reports
Lammert J, Pfarr N, Kuligin L, Mathes S, Dreyer T, Modersohn L, Metzger P, Ferber D, Kather JN, Truhn D, Adams LC, Bressem KK, Lange S, Schwamborn K, Boeker M, Kiechle M, Schatz UA, Bronger H, Tschochohei M,
Large language models-enabled digital twins for precision medicine in rare gynecological tumors.
In: NPJ Digital Medicine
Rastkhiz A, Rastkhiz A, Erb F, Schulze-Hagen M, Ulmer FT, Neumann UP, van der Kroft G, Kuhl CK, Truhn D, Lemainque T,
Preoperative arterial and venous CT radiomics for survival prediction after pylorus preserving pancreatoduodenectomy in pancreatic head cancer.
In: Scientific Reports
Veldhuizen GP, Lenz T, Cifci D, van Treeck M, Clusmann J, Chen Y, Schneider CV, Luedde T, de Leeuw PW, El-Armouche A, Truhn D, Kather JN,
Deep learning can predict cardiovascular events from liver imaging.
In: JHEP Reports: Innovation in Hepatology
Prucker P, Bressem KK, Kim SH, Weller D, Kader A, Dorfner FJ, Ziegelmayer S, Graf MM, Lemke T, Gassert F, Can E, Meddeb A, Truhn D, Hadamitzky M, Makowski MR, Adams LC, Busch F,
Privacy-Preserving Generation of Structured Lymphoma Progression Reports from Cross-sectional Imaging: A Comparative Analysis of Llama 3.3 and Llama 4.
In: Journal of Imaging Informatics in Medicine
Adams L, Busch F, Han T, Excoffier JB, Ortala M, Löser A, Aerts HJWL, Kather JN, Truhn D, Bressem K,
LongHealth: A Question Answering Benchmark with Long Clinical Documents.
In: Journal of Healthcare Informatics Research
Häntze H, Xu L, Mertens CJ, Dorfner FJ, Donle L, Busch F, Kader A, Ziegelmayer S, Bayerl N, Navab N, Rueckert D, Schnabel J, Aerts HJWL, Truhn D, Bamberg F, Weiss J, Schlett CL, Ringhof S, Niendorf T, Pischon T, Kauczor HU, Nonnenmacher T, Kröncke T, Völzke H, Schulz-Menger J, Maier-Hein K, Hering A, Prokop M, van Ginneken B, Makowski MR, Adams LC, Bressem KK,
Segmenting Whole-Body MRI and CT for Multiorgan Anatomic Structure Delineation.
In: Radiology: Artificial intelligence
Dar SUH, Seyfarth M, Ayx I, Papavassiliu T, Schoenberg SO, Siepmann RM, Laqua FC, Kahmann J, Frey N, Baeßler B, Foersch S, Truhn D, Kather JN, Engelhardt S,
Unconditional latent diffusion models memorize patient imaging data.
In: Nature Biomedical Engineering
Siepmann R, Schneider CV, von der Stueck MS, Amygdalos I, Große K, Schneider KM, Pollmanns MR, Murad M, Joy J, Kabak E, May MR, Clusmann J, Kuhl C, Nebelung S, Kather JN, Truhn D,
The Impact of Access to Clinical Guidelines on LLM-Based Treatment Recommendations for Chronic Hepatitis B.
In: Liver International: official journal of the International Association for the Study of the Liver
Neidlinger P, El Nahhas OSM, Muti HS, Lenz T, Hoffmeister M, Brenner H, van Treeck M, Langer R, Dislich B, Behrens HM, Röcken C, Foersch S, Truhn D, Marra A, Saldanha OL, Kather JN,
Benchmarking foundation models as feature extractors for weakly supervised computational pathology.
In: Nature Biomedical Engineering
Andres A, Roland M, Wickert K, Diebels S, Truhn D, Histing T, Braun B,
Predicting the effect of individual weight-bearing on tibial load and fracture healing after tibial plateau fractures-introduction of a biomechanical simulation model.
In: Frontiers in Bioengineering and Biotechnology
Vuskov R, Hermans A, Pixberg M, Müller-Hübenthal J, Brauksiepe A, Corban E, Cubukcu M, Nowak J, Kargaliev A, von der Stück M, Siepmann R, Kuhl C, Truhn D, Nebelung S,
Comprehensive deep learning-assisted multi-condition analysis of knee MRI studies improves resident radiologist performance.
In: European Radiology
Barajas Ordonez F, Xie K, Ferreira A, Siepmann R, Chargi N, Nebelung S, Truhn D, Bergé S, Bruners P, Egger J, Hölzle F, Wirth M, Kuhl C, Hinrichs-Puladi B,
Skeletal Muscle Radiation Attenuation at C3 Predicts Survival in Head and Neck Cancer.
In: Current Oncology (Toronto, Ont.)
Radke KL, Müller-Lutz A, Abrar DB, Vach M, Rubbert C, Latz D, Antoch G, Wittsack HJ, Nebelung S, Wilms LM,
Precision Through Detail: Radiomics and Windowing Techniques as Key for Detecting Dens Axis Fractures in CT Scans.
In: Diagnostics (Basel, Switzerland)
Siepmann R, Truhn D,
Author's Response to: On Evaluating GPT-4 for CHB Treatment Recommendations: Reproducibility, Vignette Design and Prompting.
In: Liver International: official journal of the International Association for the Study of the Liver
Kreutzer H, Caselitz AS, Dratsch T, Pinto Dos Santos D, Kuhl C, Truhn D, Nebelung S,
Large language model-based uncertainty-adjusted label extraction for artificial intelligence model development in upper extremity radiography.
In: European Radiology
Rashad A, Beyer M, Eftimie S, Hinrichs-Puladi B, Vladu O, Xie K, Truhn D, Thieringer FM, Gander T, Hölzle F, Egger J, Ilesan RR,
Pioneering fully automated bony orbit segmentation: an in silico nnU-Net multicentre approach.
In: International Journal of Oral and Maxillofacial Surgery
Schleid K, Alimy AR, Hoenig T, Westfechtel S, Nebelung S, Beil FT, Rolvien T,
[Differentiation of osteoarthritis phenotypes on MRI using artificial intelligence].
In: Orthopadie (Heidelberg, Germany)
Wind S, Sopa J, Truhn D, Lotfinia M, Nguyen TT, Bressem K, Adams L, Rusu M, Köstler H, Wellein G, Maier A, Tayebi Arasteh S,
Multi-step retrieval and reasoning improves radiology question answering with large language models.
In: NPJ Digital Medicine
Kather JN, Ferber D, Wiest IC, Gilbert S, Truhn D,
Large language models could make natural language again the universal interface of healthcare.
In: Nature Medicine
Ferber D, Wölflein G, Wiest IC, Ligero M, Sainath S, Ghaffari Laleh N, El Nahhas OSM, Müller-Franzes G, Jäger D, Truhn D, Kather JN,
In-context learning enables multimodal large language models to classify cancer pathology images.
In: Nature Communications
Han T, Nebelung S, Khader F, Wang T, Müller-Franzes G, Kuhl C, Försch S, Kleesiek J, Haarburger C, Bressem KK, Kather JN, Truhn D,
Medical large language models are susceptible to targeted misinformation attacks.
In: npj Digital Medicine
Wiest IC, Ferber D, Zhu J, van Treeck M, Meyer SK, Juglan R, Carrero ZI, Paech D, Kleesiek J, Ebert MP, Truhn D, Kather JN,
Privacy-preserving large language models for structured medical information retrieval.
In: npj Digital Medicine
Fast D, Adams LC, Busch F, Fallon C, Huppertz M, Siepmann R, Prucker P, Bayerl N, Truhn D, Makowski M, Löser A, Bressem KK,
Autonomous medical evaluation for guideline adherence of large language models.
In: npj Digital Medicine
Busch F, Kather JN, Johner C, Moser M, Truhn D, Adams LC, Bressem KK,
Navigating the European Union Artificial Intelligence Act for Healthcare.
In: npj Digital Medicine
Tayebi Arasteh S, Siepmann R, Huppertz M, Lotfinia M, Puladi B, Kuhl C, Truhn D, Nebelung S,
The Treasure Trove Hidden in Plain Sight: The Utility of GPT-4 in Chest Radiograph Evaluation.
In: Radiology
Adams LC, Truhn D, Busch F, Dorfner F, Nawabi J, Makowski MR, Bressem KK,
Llama 3 Challenges Proprietary State-of-the-Art Large Language Models in Radiology Board-style Examination Questions.
In: Radiology
Han T, Žigutyt˙e L, Huck L, Huppertz MS, Siepmann R, Gandelsman Y, Blüthgen C, Khader F, Kuhl C, Nebelung S, Kather JN, Truhn D,
Reconstruction of patient-specific confounders in AI-based radiologic image interpretation using generative pretraining.
In: Cell Reports Medicine
Arasteh ST, Lotfinia M, Nolte T, Saehn MJ, Isfort P, Kuhl C, Nebelung S, Kaissis G, Truhn D,
Securing Collaborative Medical AI by Using Differential Privacy: Domain Transfer for Classification of Chest Radiographs.
In: Radiology: Artificial Intelligence
Amygdalos I, Truhn D, Vondran FWR,
Outcome prediction after resection of colorectal cancer liver metastases: out with the old, in with the new?
In: Hepatobiliary Surgery and Nutrition
Josephs G, Hitpass L, Truhn D, Meister F, Berres ML, Luedde T, Jonigk D, Damink SWMO, Lang SA, Vondran F, Amygdalos I,
Splenic hypertrophy predicts liverspecific complications in patients undergoing major liver resection for colorectal liver metastases, after preoperative chemotherapy.
In: Hepatobiliary Surgery and Nutrition
Busch F, Han T, Makowski MR, Truhn D, Bressem KK, Adams L,
Integrating Text and Image Analysis: Exploring GPT-4V’s Capabilities in Advanced Radiological Applications Across Subspecialties.
In: Journal of Medical Internet Research
Lichte P, Bläsius FM, Ganse B, Gueorguiev B, Pastor T, Nebelung S, Migliorini F, Klos K, Modabber A, Scaglioni MF, Schopper C, Hildebrand F, Knobe M,
Intraoperative pneumatic tourniquet application reduces soft-tissue microcirculation, but without affecting wound healing in calcaneal fractures.
In: European Journal of Medical Research
Busch F, Hoffmann L, Truhn D, Ortiz-Prado E, Makowski MR, Bressem KK, Adams LC, COMFORT Consortium,
Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties.
In: BMC Medical Education
de Vente C, Vermeer KA, Jaccard N, Wang H, Sun H, Khader F, Truhn D, Aimyshev T, Zhanibekuly Y, Le TD, Galdran A, Ballester MAG, Carneiro G, Devika RG, Sethumadhavan HP, Puthussery D, Liu H, Yang Z, Kondo S, Kasai S, Wang E, Durvasula A, Heras J, Zapata MA, Araujo T, Aresta G, Bogunovic H, Arikan M, Lee YC, Cho HB, Choi YH, Qayyum A, Razzak I, van Ginneken B, Lemij HG, Sanchez CI.
AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.
In: IEEE Trans Med Imaging
Calderaro J, Žigutytė L, Truhn D, Jaffe A, Kather JN.
Artificial intelligence in liver cancer - new tools for research and patient management.
In: Nat Rev Gastroenterol Hepatol
Han T, Adams LC, Bressem KK, Busch F, Nebelung S, Truhn D.
Comparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions.
In: JAMA
Müller-Franzes G, Huck L, Bode M, Nebelung S, Kuhl C, Truhn D, Lemainque T.
Diffusion probabilistic versus generative adversarial models to reduce contrast agent dose in breast MRI.
In: Eur Radiol Exp
Truhn D, Tayebi Arasteh S, Saldanha OL, Müller-Franzes G, Khader F, Quirke P, West NP, Gray R, Hutchins GGA, James JA, Loughrey MB, Salto-Tellez M, Brenner H, Brobeil A, Yuan T, Chang-Claude J, Hoffmeister M, Foersch S, Han T, Keil S, Schulze-Hagen M, Isfort P, Bruners P, Kaissis G, Kuhl C, Nebelung S, Kather JN.
Encrypted federated learning for secure decentralized collaboration in cancer image analysis.
In: Med Image Analysis
Jiang X, Hoffmeister M, Brenner H, Muti HS, Yuan T, Foersch S, West NP, Brobeil A, Jonnagaddala J, Hawkins N, Ward RL, Brinker TJ, Saldanha OL, Ke J, Müller W, Grabsch HI, Quirke P, Truhn D, Kather JN.
End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study.
In: Lancet Digit Health
Tayebi Arasteh S, Misera L, Kather JN, Truhn D, Nebelung S.
Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images.
In: Eur Radiol Exp
Tietz E, Müller-Franzes G, Zimmermann M, Kuhl CK, Keil S, Nebelung S, Truhn D.
Evaluation of Pulmonary Nodules by Radiologists vs. Radiomics in Stand-Alone and Complementary CT and MRI.
In: Diagnostics (Basel)
Truhn D, Loeffler CM, Müller-Franzes G, Nebelung S, Hewitt KJ, Brandner S, Bressem KK, Foersch S, Kather JN.
Extracting structured information from unstructured histopathology reports using generative pre-trained transformer 4 (GPT-4).
In: J Pathol
Motmaen I, Xie K, Schönbrunn L, Berens J, Grunert K, Plum AM, Raufeisen J, Ferreira A, Hermans A, Egger J, Hölzle F, Truhn D, Puladi B.
Insights into Predicting Tooth Extraction from Panoramic Dental Images: Artificial Intelligence vs. Dentists.
In: Clin Oral Investig
Busch F, Hoffmann L, Truhn D, Palaian S, Alomar M, Shpati K, Makowski MR, Bressem KK, Adams LC.
International pharmacy students' perceptions towards artificial intelligence in medicine-A multinational, multicentre cross-sectional study.
In: Br J Clin Pharmacol
Müller-Franzes G, Khader F, Tayebi Arasteh S, Huck L, Bode M, Han T, Lemainque T, Kather JN, Nebelung S, Kuhl C, Truhn D.
Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization.
In: Radiology
Truhn D, Eckardt JN, Ferber D, Kather JN.
Large language models and multimodal foundation models for precision oncology.
In: NPJ Precis Oncol
Tayebi Arasteh S, Han T, Lotfinia M, Kuhl C, Kather JN, Truhn D, Nebelung S.
Large language models streamline automated machine learning for clinical studies.
In: Nat Commun
Elmaagacli S, Thiele C, Meister F, Menne P, Truhn D, Olde Damink SWM, Bickenbach J, Neumann U, Lang SA, Vondran F, Amygdalos I.
Preoperative three-dimensional lung volumetry predicts respiratory complications in patients undergoing major liver resection for colorectal metastases.
In: Sci Rep
Tayebi Arasteh S, Ziller A, Kuhl C, Makowski M, Nebelung S, Braren R, Rueckert D, Truhn D, Kaissis G.
Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging.
In: Commun Med (Lond)
Kolbinger FR, Veldhuizen GP, Zhu J, Truhn D, Kather JN.
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis.
In: Commun Med (Lond)
Truhn D, Müller-Franzes G, Kather JN.
The ecological footprint of medical AI.
In: Eur Radiol
Siepmann R, Huppertz M, Rastkhiz A, Reen M, Corban E, Schmidt C, Wilke S, Schad P, Yüksel C, Kuhl C, Truhn D, Nebelung S.
The virtual reference radiologist: comprehensive AI assistance for clinical image reading and interpretation.
In: Eur Radiol
Lemainque T, Pridöhl N, Zhang S, Huppertz M, Post M, Yüksel C, Yoneyama M, Prescher A, Kuhl C, Truhn D, Nebelung S.
Time-efficient combined morphologic and quantitative joint MRI: an in situ study of standardized knee cartilage defects in human cadaveric specimens.
In: Eur Radiol Exp
Lemainque T, Pridöhl N, Huppertz M, Post M, Yüksel C, Siepmann R, Radke KL, Zhang S, Yoneyama M, Prescher A, Kuhl C, Truhn D, Nebelung S.
Two for One-Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform.
In: Diagnostics (Basel)
Niehues JM, Müller-Franzes G, Schirris Y, Wagner SJ, Jendrusch M, Kloor M, Pearson AT, Muti HS, Hewitt KJ, Veldhuizen GP, Zigutyte L, Truhn D, Kather JN.
Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance.
In: Comput Biol Med
Misera L, Müller-Franzes G, Truhn D, Kather JN.
Weakly Supervised Deep Learning in Radiology.
In: Radiology
Braun BJ, Histing T, Menger MM, Herath SC, Mueller-Franzes GA, Grimm B, Marmor MT, Truhn D; AO Smart Digital Solutions Task Force (Andrew M Hanflik, Peter H Richter, Sureshan Sivananthan, Seth R Yarboro).
Wearable activity data can predict functional recovery after musculoskeletal injury: Feasibility of a machine learning approach.
In: Injury
Braun EM, Juhasz-Böss I, Solomayer EF, Truhn D, Keller C, Heinrich V, Braun BJ.
Will I soon be out of my job? Quality and guideline conformity of ChatGPT therapy suggestions to patient inquiries with gynecologic symptoms in a palliative setting.
In: Arch Gynecol Obstet
Lemainque T, Huppertz MS, Yüksel C, Siepmann R, Kuhl C, Roemer F, Truhn D, Nebelung S.
[Current MR imaging of cartilage in the context of knee osteoarthritis (part 1) : Principles and sequences].
In: Radiologie (Heidelb)
Huppertz MS, Lemainque T, Yüksel C, Siepmann R, Kuhl C, Roemer F, Truhn D, Nebelung S,
[Current MR imaging of cartilage in the context of knee osteoarthritis (part 2) : Cartilage pathologies and their assessment].
In: Radiologie (Heidelberg, Germany)
Wilms LM, Radke KL, Abrar DB, Frahm J, Voit D, Thelen S, Klee D, Grunz JP, Müller-Lutz A, Nebelung S,
Dynamic assessment of scapholunate ligament status by real-time magnetic resonance imaging: an exploratory clinical study.
In: Skeletal radiology
Tayebi Arasteh S, Kuhl C, Saehn MJ, Isfort P, Truhn D, Nebelung S,
Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning.
In: Scientific reports
Truhn D, Weber CD, Braun BJ, Bressem K, Kather JN, Kuhl C, Nebelung S,
A pilot study on the efficacy of GPT-4 in providing orthopedic treatment recommendations from MRI reports.
In: Scientific reports
Tayebi Arasteh S, Romanowicz J, Pace DF, Golland P, Powell AJ, Maier AK, Truhn D, Brosch T, Weese J, Lotfinia M, van der Geest RJ, Moghari MH,
Automated segmentation of 3D cine cardiovascular magnetic resonance imaging.
In: Frontiers in cardiovascular medicine
Muti HS, Röcken C, Behrens HM, Löffler CML, Reitsam NG, Grosser B, Märkl B, Stange DE, Jiang X, Velduizen GP, Truhn D, Ebert MP, Grabsch HI, Kather JN,
Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study.
In: European journal of cancer (Oxford, England : 1990)
Truhn D, Reis-Filho JS, Kather JN,
Large language models should be used as scientific reasoning engines, not knowledge databases.
In: Nature medicine
Khader F, Müller-Franzes G, Wang T, Han T, Tayebi Arasteh S, Haarburger C, Stegmaier J, Bressem K, Kuhl C, Nebelung S, Kather JN, Truhn D,
Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers.
In: Radiology
Wagner SJ, Reisenbüchler D, West NP, Niehues JM, Zhu J, Foersch S, Veldhuizen GP, Quirke P, Grabsch HI, van den Brandt PA, Hutchins GGA, Richman SD, Yuan T, Langer R, Jenniskens JCA, Offermans K, Mueller W, Gray R, Gruber SB, Greenson JK, Rennert G, Bonner JD, Schmolze D, Jonnagaddala J, Hawkins NJ, Ward RL, Morton D, Seymour M, Magill L, Nowak M, Hay J, Koelzer VH, Church DN, Matek C, Geppert C, Peng C, Zhi C, Ouyang X, James JA, Loughrey MB, Salto-Tellez M, Brenner H, Hoffmeister M, Truhn D, Schnabel JA, Boxberg M, Peng T, Kather JN,
Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.
In: Cancer cell
Müller-Franzes G, Müller-Franzes F, Huck L, Raaff V, Kemmer E, Khader F, Arasteh ST, Lemainque T, Kather JN, Nebelung S, Kuhl C, Truhn D,
Fibroglandular tissue segmentation in breast MRI using vision transformers: a multi-institutional evaluation.
In: Scientific reports
Müller-Franzes G, Niehues JM, Khader F, Arasteh ST, Haarburger C, Kuhl C, Wang T, Han T, Nolte T, Nebelung S, Kather JN, Truhn D,
A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis.
In: Scientific reports
Khader F, Kather JN, Müller-Franzes G, Wang T, Han T, Tayebi Arasteh S, Hamesch K, Bressem K, Haarburger C, Stegmaier J, Kuhl C, Nebelung S, Truhn D,
Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data.
In: Scientific reports
Jiang X, Zhao H, Saldanha OL, Nebelung S, Kuhl C, Amygdalos I, Lang SA, Wu X, Meng X, Truhn D, Kather JN, Ke J,
An MRI Deep Learning Model Predicts Outcome in Rectal Cancer.
In: Radiology
Frenken M, Radke KL, Schäfer ELE, Valentin B, Wilms LM, Abrar DB, Nebelung S, Martirosian P, Wittsack HJ, Müller-Lutz A,
Insights into the Age Dependency of Compositional MR Biomarkers Quantifying the Health Status of Cartilage in Metacarpophalangeal Joints.
In: Diagnostics (Basel, Switzerland)
Khader F, Müller-Franzes G, Tayebi Arasteh S, Han T, Haarburger C, Schulze-Hagen M, Schad P, Engelhardt S, Baeßler B, Foersch S, Stegmaier J, Kuhl C, Nebelung S, Kather JN, Truhn D,
Denoising diffusion probabilistic models for 3D medical image generation.
In: Scientific reports
Tayebi Arasteh S, Isfort P, Saehn M, Mueller-Franzes G, Khader F, Kather JN, Kuhl C, Nebelung S, Truhn D,
Collaborative training of medical artificial intelligence models with non-uniform labels.
In: Scientific reports
Belger E, Truhn D, Weber CD, Neumann UP, Hildebrand F, Horst K,
The Impact of Body Mass Composition on Outcome in Multiple Traumatized Patients-Results from the Fourth Thoracic and Third Lumbar Vertebrae: A Single-Center Retrospective Observational Study.
In: Journal of clinical medicine
Wolff LI, Hachgenei E, Goßmann P, Druzenko M, Frye M, König N, Schmitt RH, Chrysos A, Jöchle K, Truhn D, Kather JN, Lambertz A, Gaisa NT, Jonigk D, Ulmer TF, Neumann UP, Lang SA, Amygdalos I,
Optical coherence tomography combined with convolutional neural networks can differentiate between intrahepatic cholangiocarcinoma and liver parenchyma ex vivo.
In: Journal of cancer research and clinical oncology
Adams LC, Truhn D, Busch F, Kader A, Niehues SM, Makowski MR, Bressem KK,
Leveraging GPT-4 for Post Hoc Transformation of Free-text Radiology Reports into Structured Reporting: A Multilingual Feasibility Study.
In: Radiology
Busch F, Xu L, Sushko D, Weidlich M, Truhn D, Müller-Franzes G, Heimer MM, Niehues SM, Makowski MR, Hinsche M, Vahldiek JL, Aerts HJ, Adams LC, Bressem KK,
Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs.
In: Computer methods and programs in biomedicine
Niehues JM, Quirke P, West NP, Grabsch HI, van Treeck M, Schirris Y, Veldhuizen GP, Hutchins GGA, Richman SD, Foersch S, Brinker TJ, Fukuoka J, Bychkov A, Uegami W, Truhn D, Brenner H, Brobeil A, Hoffmeister M, Kather JN,
Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study.
In: Cell reports. Medicine
Müller-Franzes G, Huck L, Tayebi Arasteh S, Khader F, Han T, Schulz V, Dethlefsen E, Kather JN, Nebelung S, Nolte T, Kuhl C, Truhn D,
Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images.
In: Radiology
Adams LC, Busch F, Truhn D, Makowski MR, Aerts HJWL, Bressem KK,
What Does DALL-E 2 Know About Radiology?
In: Journal of medical Internet research
Pastor T, Zderic I, van Knegsel KP, Beeres FJP, Migliorini F, Babst R, Nebelung S, Ganse B, Schoeneberg C, Gueorguiev B, Knobe M,
Biomechanical analysis of helical versus straight plating of proximal third humeral shaft fractures.
In: Archives of orthopaedic and trauma surgery
Bode M, Charlotte Huck L, Zhang S, Nolte T, Yoneyama M, Nebelung S, Katharina Kuhl C,
Clinical evaluation of cylindrical regional suppression in dynamic contrast-enhanced breast MRI: An intra-individual comparison study on image quality and lesion conspicuity.
In: European journal of radiology
Nolte T, Westfechtel S, Schock J, Knobe M, Pastor T, Pfaehler E, Kuhl C, Truhn D, Nebelung S,
Getting Cartilage Thickness Measurements Right: A Systematic Inter-Method Comparison Using MRI Data from the Osteoarthritis Initiative.
In: Cartilage
Khader F, Han T, Müller-Franzes G, Huck L, Schad P, Keil S, Barzakova E, Schulze-Hagen M, Pedersoli F, Schulz V, Zimmermann M, Nebelung L, Kather J, Hamesch K, Haarburger C, Marx G, Stegmaier J, Kuhl C, Bruners P, Nebelung S, Truhn D,
Artificial Intelligence for Clinical Interpretation of Bedside Chest Radiographs.
In: Radiology
Saldanha OL, Muti HS, Grabsch HI, Langer R, Dislich B, Kohlruss M, Keller G, van Treeck M, Hewitt KJ, Kolbinger FR, Veldhuizen GP, Boor P, Foersch S, Truhn D, Kather JN,
Direct prediction of genetic aberrations from pathology images in gastric cancer with swarm learning.
In: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Amygdalos I, Müller-Franzes G, Bednarsch J, Czigany Z, Ulmer TF, Bruners P, Kuhl C, Neumann UP, Truhn D, Lang SA,
Novel machine learning algorithm can identify patients at risk of poor overall survival following curative resection for colorectal liver metastases.
In: Journal of hepato-biliary-pancreatic sciences
Pastor T, Kastner P, Souleiman F, Gehweiler D, Migliorini F, Link BC, Beeres FJP, Babst R, Nebelung S, Ganse B, Schoeneberg C, Gueorguiev B, Knobe M,
Anatomical analysis of different helical plate designs for proximal humeral shaft fracture fixation.
In: European journal of trauma and emergency surgery : official publication of the European Trauma Society
Zanderigo E, Huck L, Distelmaier M, Dethlefsen E, Maywald M, Truhn D, Dirrichs T, Doneva M, Schulz V, Kuhl CK, Nolte T,
Feasibility study of 2D Dixon-Magnetic Resonance Fingerprinting (MRF) of breast cancer.
In: European journal of radiology open
Ghaffari Laleh N, Truhn D, Veldhuizen GP, Han T, van Treeck M, Buelow RD, Langer R, Dislich B, Boor P, Schulz V, Kather JN,
Adversarial attacks and adversarial robustness in computational pathology.
In: Nature communications
Ghaffari Laleh N, Muti HS, Loeffler CML, Echle A, Saldanha OL, Mahmood F, Lu MY, Trautwein C, Langer R, Dislich B, Buelow RD, Grabsch HI, Brenner H, Chang-Claude J, Alwers E, Brinker TJ, Khader F, Truhn D, Gaisa NT, Boor P, Hoffmeister M, Schulz V, Kather JN,
Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474.
In: Medical image analysis
Wilms LM, Radke KL, Latz D, Thiel TA, Frenken M, Kamp B, Filler TJ, Nagel AM, Müller-Lutz A, Abrar DB, Nebelung S,
UTE-T2* versus conventional T2* mapping to assess posterior cruciate ligament ultrastructure and integrity-an in-situ study.
In: Quantitative imaging in medicine and surgery
Bode M, Charlotte Huck L, Raaff V, Hitpass L, Braunschweig T, Nebelung S, Katharina Kuhl C,
Digital breast tomosynthesis-guided vacuum-assisted biopsy of suspicious calcifications at different sites within one breast: Is biopsy of more than one location needed?
In: European journal of radiology
Yüksel C, Sähn MJ, Kleines M, Brokmann JC, Kuhl CK, Truhn D, Ritter A, Isfort P, Schulze-Hagen MF,
Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2.
In: RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Ciba M, Winkelmeyer EM, Schock J, Westfechtel S, Nolte T, Knobe M, Prescher A, Kuhl C, Truhn D, Nebelung S,
Varus stress MRI in the refined assessment of the posterolateral corner of the knee joint.
In: Scientific reports
Kather JN, Ghaffari Laleh N, Foersch S, Truhn D,
Medical domain knowledge in domain-agnostic generative AI.
In: NPJ digital medicine
Radke KL, Wilms LM, Frenken M, Stabinska J, Knet M, Kamp B, Thiel TA, Filler TJ, Nebelung S, Antoch G, Abrar DB, Wittsack HJ, Müller-Lutz A,
Lorentzian-Corrected Apparent Exchange-Dependent Relaxation (LAREX) Ω-Plot Analysis-An Adaptation for qCEST in a Multi-Pool System: Comprehensive In Silico, In Situ, and In Vivo Studies.
In: International journal of molecular sciences
Radke KL, Abrar DB, Frenken M, Wilms LM, Kamp B, Boschheidgen M, Liebig P, Ljimani A, Filler TJ, Antoch G, Nebelung S, Wittsack HJ, Müller-Lutz A,
Chemical Exchange Saturation Transfer for Lactate-Weighted Imaging at 3 T MRI: Comprehensive In Silico, In Vitro, In Situ, and In Vivo Evaluations.
In: Tomography (Ann Arbor, Mich.)
Ghaffari Laleh N, Muti HS, Loeffler CML, Echle A, Saldanha OL, Mahmood F, Lu MY, Trautwein C, Langer R, Dislich B, Buelow RD, Grabsch HI, Brenner H, Chang-Claude J, Alwers E, Brinker TJ, Khader F, Truhn D, Gaisa NT, Boor P, Hoffmeister M, Schulz V, Kather JN,
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.
In: Medical image analysis
Huck LC, Truhn D, Wilpert C, Zanderigo E, Raaff V, Dethlefsen E, Bode M, Kuhl CK,
Background parenchymal enhancement in contrast-enhanced MR imaging suggests systemic effects of intrauterine contraceptive devices.
In: European radiology
Saldanha OL, Quirke P, West NP, James JA, Loughrey MB, Grabsch HI, Salto-Tellez M, Alwers E, Cifci D, Ghaffari Laleh N, Seibel T, Gray R, Hutchins GGA, Brenner H, van Treeck M, Yuan T, Brinker TJ, Chang-Claude J, Khader F, Schuppert A, Luedde T, Trautwein C, Muti HS, Foersch S, Hoffmeister M, Truhn D, Kather JN,
Swarm learning for decentralized artificial intelligence in cancer histopathology.
In: Nature medicine
Pastor T, Beeres FJP, Kastner P, Gehweiler D, Migliorini F, Nebelung S, Scaglioni MF, Souleiman F, Link BC, Babst R, Gueorguiev B, Knobe M,
Anatomical analysis of different helical plate designs for distal femoral fracture fixation.
In: Injury
Müller-Franzes G, Nolte T, Ciba M, Schock J, Khader F, Prescher A, Wilms LM, Kuhl C, Nebelung S, Truhn D,
Fast, Accurate, and Robust T2 Mapping of Articular Cartilage by Neural Networks.
In: Diagnostics (Basel, Switzerland)
Frenken M, Rübsam G, Mewes A, Radke KL, Li L, Wilms LM, Nebelung S, Abrar DB, Sewerin P,
To Contrast or Not to Contrast? On the Role of Contrast Enhancement in Hand MRI Studies of Patients with Rheumatoid Arthritis.
In: Diagnostics (Basel, Switzerland)
Müller-Franzes G, Nebelung S, Schock J, Haarburger C, Khader F, Pedersoli F, Schulze-Hagen M, Kuhl C, Truhn D,
Reliability as a Precondition for Trust-Segmentation Reliability Analysis of Radiomic Features Improves Survival Prediction.
In: Diagnostics (Basel, Switzerland)
Kubo Y, Beckmann R, Fragoulis A, Conrads C, Pavanram P, Nebelung S, Wolf M, Wruck CJ, Jahr H, Pufe T,
Nrf2/ARE Signaling Directly Regulates SOX9 to Potentially Alter Age-Dependent Cartilage Degeneration.
In: Antioxidants (Basel, Switzerland)
Duong F, Gadermayr M, Merhof D, Kuhl C, Bruners P, Loosen SH, Roderburg C, Truhn D, Schulze-Hagen MF,
Automated major psoas muscle volumetry in computed tomography using machine learning algorithms.
In: International journal of computer assisted radiology and surgery
van de Wall BJM, Beeres FJP, Rompen IF, Link BC, Babst R, Schoeneberg C, Michelitsch C, Nebelung S, Pape HC, Gueorguiev B, Knobe M,
RIA versus iliac crest bone graft harvesting: A meta-analysis and systematic review.
In: Injury
Schrammen PL, Ghaffari Laleh N, Echle A, Truhn D, Schulz V, Brinker TJ, Brenner H, Chang-Claude J, Alwers E, Brobeil A, Kloor M, Heij LR, Jäger D, Trautwein C, Grabsch HI, Quirke P, West NP, Hoffmeister M, Kather JN,
Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology.
In: The Journal of pathology
Frenken M, Schleich C, Radke KL, Müller-Lutz A, Benedikter C, Franz A, Antoch G, Bittersohl B, Abrar DB, Nebelung S,
Imaging of exercise-induced spinal remodeling in elite rowers.
In: Journal of science and medicine in sport
Kamp B, Frenken M, Henke JM, Abrar DB, Nagel AM, Gast LV, Oeltzschner G, Wilms LM, Nebelung S, Antoch G, Wittsack HJ, Müller-Lutz A,
Quantification of Sodium Relaxation Times and Concentrations as Surrogates of Proteoglycan Content of Patellar CARTILAGE at 3T MRI.
In: Diagnostics (Basel, Switzerland)
Schock J, Truhn D, Nürnberger D, Conrad S, Huppertz MS, Keil S, Kuhl C, Merhof D, Nebelung S,
Artificial intelligence-based automatic assessment of lower limb torsion on MRI.
In: Scientific reports
Haarburger C, Müller-Franzes G, Weninger L, Kuhl C, Truhn D, Merhof D,
Author Correction: Radiomics feature reproducibility under inter-rater variability in segmentations of CT images.
In: Scientific reports
Wilms LM, Radke KL, Abrar DB, Latz D, Schock J, Frenken M, Windolf J, Antoch G, Filler TJ, Nebelung S,
Micro- and Macroscale Assessment of Posterior Cruciate Ligament Functionality Based on Advanced MRI Techniques.
In: Diagnostics (Basel, Switzerland)
Wollschläger LM, Radke KL, Schock J, Kotowski N, Latz D, Kanschik D, Filler TJ, Caspers S, Antoch G, Windolf J, Abrar DB, Nebelung S,
The MRI posterior drawer test to assess posterior cruciate ligament functionality and knee joint laxity.
In: Scientific reports
van Knegsel KP, Ganse B, Haefeli PC, Migliorini F, Scaglioni MF, van de Wall BJM, Kim BS, Link BC, Beeres FJP, Nebelung S, Schoeneberg C, Hildebrand F, Gueorguiev B, Knobe M,
Trochanteric Femur Fractures: Application of Skeletal Traction during Surgery Does Not Alter Soft-Tissue Microcirculation.
In: Medicina (Kaunas, Lithuania)
Tietz E, Truhn D, Müller-Franzes G, Berres ML, Hamesch K, Lang SA, Kuhl CK, Bruners P, Schulze-Hagen M,
A Radiomics Approach to Predict the Emergence of New Hepatocellular Carcinoma in Computed Tomography for High-Risk Patients with Liver Cirrhosis.
In: Diagnostics (Basel, Switzerland)
Kurt B, Buendgens L, Wirtz TH, Loosen SH, Schulze-Hagen M, Truhn D, Brozat JF, Abu Jhaisha S, Hohlstein P, Koek G, Weiskirchen R, Trautwein C, Tacke F, Hamesch K, Koch A,
Serum Perilipin 2 (PLIN2) Predicts Multiple Organ Dysfunction in Critically Ill Patients.
In: Biomedicines
Link BC, van Veelen NM, Boernert K, Kittithamvongs P, Beeres FJP, de Boer HH, Migliorini F, Nebelung S, Knobe M, Ruchholtz S, Babst R, Jiamton C,
The radiographic relationship between the cortical overlap view (COV) and the tip of the greater trochanter.
In: Scientific reports
Said O, Schock J, Abrar DB, Schad P, Kuhl C, Nolte T, Knobe M, Prescher A, Truhn D, Nebelung S,
In-Situ Cartilage Functionality Assessment Based on Advanced MRI Techniques and Precise Compartmental Knee Joint Loading through Varus and Valgus Stress.
In: Diagnostics (Basel, Switzerland)
Ciba M, Winkelmeyer EM, Schock J, Schad P, Kotowski N, Nolte T, Wollschläger LM, Knobe M, Prescher A, Kuhl C, Truhn D, Nebelung S,
Comprehensive Assessment of Medial Knee Joint Instability by Valgus Stress MRI.
In: Diagnostics (Basel, Switzerland)
Knobe M, Iselin LD, van de Wall BJM, Lichte P, Hildebrand F, Beeres FJP, Link BC, Gueorguiev B, Nebelung S, Ganse B, Migliorini F, Klos K, Babst R, Haefeli PC,
Reduced pre-operative skin oxygen saturation predicts revision after open reduction and internal fixation in calcaneal fractures : A reduced pre-operative oxygen saturation as measured by laser-Doppler spectrophotometry in 8 mm depth is associated with revision surgery after open reduction and internal fixation of calcaneal fractures through an extended lateral approach.
In: International orthopaedics
Said O, Schock J, Krämer N, Thüring J, Hitpass L, Schad P, Kuhl C, Abrar D, Truhn D, Nebelung S,
Correction to: An MRI‑compatible varus-valgus loading device for whole‑knee joint functionality assessment based on compartmental compression: a proof‑of‑concept study.
In: Magma (New York, N.Y.)
Han T, Nebelung S, Pedersoli F, Zimmermann M, Schulze-Hagen M, Ho M, Haarburger C, Kiessling F, Kuhl C, Schulz V, Truhn D,
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization.
In: Nature communications
Li J, Nebelung S, Schock J, Rath B, Tingart M, Liu Y, Siroros N, Eschweiler J,
A Novel Combined Level Set Model for Carpus Segmentation from Magnetic Resonance Images with Prior Knowledge aligned in Polar Coordinate System.
In: Computer methods and programs in biomedicine
Gadermayr M, Heckmann L, Li K, Bähr F, Müller M, Truhn D, Merhof D, Gess B,
Image-to-Image Translation for Simplified MRI Muscle Segmentation.
In: Frontiers in radiology
Radke KL, Wollschläger LM, Nebelung S, Abrar DB, Schleich C, Boschheidgen M, Frenken M, Schock J, Klee D, Frahm J, Antoch G, Thelen S, Wittsack HJ, Müller-Lutz A,
Deep Learning-Based Post-Processing of Real-Time MRI to Assess and Quantify Dynamic Wrist Movement in Health and Disease.
In: Diagnostics (Basel, Switzerland)
Winkelmeyer EM, Schock J, Wollschläger LM, Schad P, Huppertz MS, Kotowski N, Prescher A, Kuhl C, Truhn D, Nebelung S,
Seeing Beyond Morphology-Standardized Stress MRI to Assess Human Knee Joint Instability.
In: Diagnostics (Basel, Switzerland)
Rompen IF, Knobe M, Link BC, Beeres FJP, Baumgaertner R, Diwersi N, Migliorini F, Nebelung S, Babst R, van de Wall BJM,
Cement augmentation for trochanteric femur fractures: A meta-analysis of randomized clinical trials and observational studies.
In: PloS one
Wollschläger LM, Nebelung S, Schleich C, Müller-Lutz A, Radke KL, Frenken M, Boschheidgen M, Prost M, Antoch G, Konieczny MR, Abrar DB,
Evaluating Lumbar Intervertebral Disc Degeneration on a Compositional Level Using Chemical Exchange Saturation Transfer: Preliminary Results in Patients with Adolescent Idiopathic Scoliosis.
In: Diagnostics (Basel, Switzerland)
Schopper C, Keck K, Zderic I, Migliorini F, Link BC, Beeres FJP, Babst R, Nebelung S, Eschbach D, Knauf T, Ganse B, Schoeneberg C, Hildebrand F, Gueorguiev B, Knobe M,
Screw-blade fixation systems for implant anchorage in the femoral head: Horizontal blade orientation provides superior stability.
In: Injury
Truhn D, Zwingenberger KT, Schock J, Abrar DB, Radke KL, Post M, Linka K, Knobe M, Kuhl C, Nebelung S,
No pressure, no diamonds? - Static vs. dynamic compressive in-situ loading to evaluate human articular cartilage functionality by functional MRI.
In: Journal of the mechanical behavior of biomedical materials
Schock J, Truhn D, Abrar DB, Merhof D, Conrad S, Post M, Mittelstrass F, Kuhl C, Nebelung S,
Automated Analysis of Alignment in Long-Leg Radiographs by Using a Fully Automated Support System Based on Artificial Intelligence.
In: Radiology. Artificial intelligence
Huppertz MS, Schock J, Radke KL, Abrar DB, Post M, Kuhl C, Truhn D, Nebelung S,
Longitudinal T2 Mapping and Texture Feature Analysis in the Detection and Monitoring of Experimental Post-Traumatic Cartilage Degeneration.
In: Life (Basel, Switzerland)
Liebl M, Pedersoli F, Zimmermann M, Schulze-Hagen M, Truhn D, Sieben P, von Stillfried S, Tschinaev A, Heinzel A, Kuhl CK, Bruners P, Isfort P,
Induction of Contralateral Hepatic Hypertrophy by Unilobar Yttrium-90 Transarterial Radioembolization versus Portal Vein Embolization: An Animal Study.
In: Journal of vascular and interventional radiology : JVIR
Frenken M, Nebelung S, Schleich C, Müller-Lutz A, Radke KL, Kamp B, Boschheidgen M, Wollschläger L, Bittersohl B, Antoch G, Konieczny MR, Abrar DB,
Non-Specific Low Back Pain and Lumbar Radiculopathy: Comparison of Morphologic and Compositional MRI as Assessed by gagCEST Imaging at 3T.
In: Diagnostics (Basel, Switzerland)
Bähr FS, Gess B, Müller M, Romanzetti S, Gadermayr M, Kuhl C, Nebelung S, Schulz JB, Dohrn MF,
Semi-Automatic MRI Muscle Volumetry to Diagnose and Monitor Hereditary and Acquired Polyneuropathies.
In: Brain sciences
Linka K, Thüring J, Rieppo L, Aydin RC, Cyron CJ, Kuhl C, Merhof D, Truhn D, Nebelung S,
Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition.
In: Osteoarthritis and cartilage
Abrar DB, Schleich C, Frenken M, Vordenbäumen S, Richter J, Schneider M, Ostendorf B, Nebelung S, Sewerin P,
DGEMRIC in the Assessment of Pre-Morphological Cartilage Degeneration in Rheumatic Disease: Rheumatoid Arthritis vs. Psoriatic Arthritis.
In: Diagnostics (Basel, Switzerland)
Proske A, Link BC, Beeres FJP, Nebelung S, Füchtmeier B, Knobe M,
[Erratum to: Residency program under scrutiny (part 2)-How do residents prepare for emergency operations?].
In: Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen
Proske A, Link BC, Beeres F, Nebelung S, Füchtmeier B, Knobe M,
[Residency program under scrutiny (part 2)-How do residents prepare for emergency operations?].
In: Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen
Abrar DB, Schleich C, Brinks R, Goertz C, Schneider M, Nebelung S, Sewerin P,
Differentiating rheumatoid and psoriatic arthritis: a systematic analysis of high-resolution magnetic resonance imaging features-preliminary findings.
In: Skeletal radiology
Abrar DB, Schleich C, Radke KL, Frenken M, Stabinska J, Ljimani A, Wittsack HJ, Antoch G, Bittersohl B, Hesper T, Nebelung S, Müller-Lutz A,
Detection of early cartilage degeneration in the tibiotalar joint using 3 T gagCEST imaging: a feasibility study.
In: Magma (New York, N.Y.)
Müller-Lutz A, Kamp B, Nagel AM, Ljimani A, Abrar D, Schleich C, Wollschläger L, Nebelung S, Wittsack HJ,
Sodium MRI of human articular cartilage of the wrist: a feasibility study on a clinical 3T MRI scanner.
In: Magma (New York, N.Y.)
Cremerius C, Gradl-Dietsch G, Beeres FJP, Link B-, Hitpaß L, Nebelung S, Horst K, Weber CD, Neuerburg C, Eschbach D, Bliemel C, Knobe M,
Team-based learning for teaching musculoskeletal ultrasound skills: a prospective randomised trial.
In: European journal of trauma and emergency surgery : official publication of the European Trauma Society
Abrar DB, Schleich C, Brinks R, Goertz C, Frenken M, Schneider M, Nebelung S, Sewerin P,
Introduction of a Simplified Psoriatic Arthritis Magnetic Resonance Imaging Score (sPsAMRIS): A Potential Tool for Treatment Monitoring in Peripheral Psoriatic Arthritis.
In: Diagnostics (Basel, Switzerland)
Han T, Nebelung S, Haarburger C, Horst N, Reinartz S, Merhof D, Kiessling F, Schulz V, Truhn D,
Breaking medical data sharing boundaries by using synthesized radiographs.
In: Science advances
Hafner T, Post M, Said O, Schad P, Schock J, Abrar DB, Knobe M, Kuhl C, Truhn D, Nebelung S,
Identifying the imaging correlates of cartilage functionality based on quantitative MRI mapping - The collagenase exposure model.
In: Acta biomaterialia
Schad P, Wollenweber M, Thüring J, Schock J, Eschweiler J, Palm G, Radermacher K, Eckstein F, Prescher A, Kuhl C, Truhn D, Nebelung S,
Magnetic resonance imaging of human knee joint functionality under variable compressive in-situ loading and axis alignment.
In: Journal of the mechanical behavior of biomedical materials
Abrar DB, Schleich C, Tsiami S, Müller-Lutz A, Radke KL, Holthausen N, Frenken M, Boschheidgen M, Antoch G, Mucke J, Sewerin P, Braun J, Nebelung S, Baraliakos X,
Functional MR imaging beyond structure and inflammation-radiographic axial spondyloarthritis is associated with proteoglycan depletion of the lumbar spine.
In: Arthritis research & therapy
Hafner T, Schock J, Post M, Abrar DB, Sewerin P, Linka K, Knobe M, Kuhl C, Truhn D, Nebelung S,
A serial multiparametric quantitative magnetic resonance imaging study to assess proteoglycan depletion of human articular cartilage and its effects on functionality.
In: Scientific reports
Haarburger C, Müller-Franzes G, Weninger L, Kuhl C, Truhn D, Merhof D,
Radiomics feature reproducibility under inter-rater variability in segmentations of CT images.
In: Scientific reports
Abrar DB, Schleich C, Nebelung S, Frenken M, Ullrich T, Radke KL, Antoch G, Vordenbäumen S, Brinks R, Schneider M, Ostendorf B, Sewerin P,
Proteoglycan loss in the articular cartilage is associated with severity of joint inflammation in psoriatic arthritis-a compositional magnetic resonance imaging study.
In: Arthritis research & therapy
Said O, Schock J, Krämer N, Thüring J, Hitpass L, Schad P, Kuhl C, Abrar D, Truhn D, Nebelung S,
An MRI-compatible varus-valgus loading device for whole-knee joint functionality assessment based on compartmental compression: a proof-of-concept study.
In: Magma (New York, N.Y.)
Thüring J, Rippel O, Haarburger C, Merhof D, Schad P, Bruners P, Kuhl CK, Truhn D,
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach.
In: European radiology experimental
Kuhl CK, Truhn D,
The Long Route to Standardized Radiomics: Unraveling the Knot from the End.
In: Radiology
Abrar DB, Schleich C, Nebelung S, Frenken M, Radke KL, Vordenbäumen S, Brinks R, Schneider M, Ostendorf B, McGonagle D, Sewerin P,
High-resolution MRI of flexor tendon pulleys using a 16-channel hand coil: disease detection and differentiation of psoriatic and rheumatoid arthritis.
In: Arthritis research & therapy
Nebelung S, Dötsch L, Shah D, Abrar DB, Linka K, Knobe M, Sewerin P, Thüring J, Kuhl C, Truhn D,
Functional MRI Mapping of Human Meniscus Functionality and its Relation to Degeneration.
In: Scientific reports
Schulze-Hagen M, Truhn D, Duong F, Keil S, Pedersoli F, Kuhl CK, Lurje G, Neumann U, Isfort P, Bruners P, Zimmermann M,
Correlation Between Sarcopenia and Growth Rate of the Future Liver Remnant After Portal Vein Embolization in Patients with Colorectal Liver Metastases.
In: Cardiovascular and interventional radiology
Nolte T, Gross-Weege N, Doneva M, Koken P, Elevelt A, Truhn D, Kuhl C, Schulz V,
Spiral blurring correction with water-fat separation for magnetic resonance fingerprinting in the breast.
In: Magnetic resonance in medicine
Truhn D, Brill N, Braun B, Merhof D, Kuhl C, Knobe M, Thüring J, Nebelung S,
A multi-purpose force-controlled loading device for cartilage and meniscus functionality assessment using advanced MRI techniques.
In: Journal of the mechanical behavior of biomedical materials
Bläsius FM, Link BC, Beeres FJP, Iselin LD, Leu BM, Gueorguiev B, Klos K, Ganse B, Nebelung S, Modabber A, Eschbach D, Weber CD, Horst K, Knobe M,
Impact of surgical procedures on soft tissue microcirculation in calcaneal fractures: A prospective longitudinal cohort study.
In: Injury
Nebelung S, Post M, Knobe M, Shah D, Schleich C, Hitpass L, Kuhl C, Thüring J, Truhn D,
Human articular cartilage mechanosensitivity is related to histological degeneration - a functional MRI study.
In: Osteoarthritis and cartilage
Truhn D, Sondern B, Oehrl S, Tingart M, Knobe M, Merhof D, Kuhl C, Thüring J, Nebelung S,
Differentiation of human cartilage degeneration by functional MRI mapping-an ex vivo study.
In: European radiology
Linka K, Schäfer A, Hillgärtner M, Itskov M, Knobe M, Kuhl C, Hitpass L, Truhn D, Thuering J, Nebelung S,
Towards Patient-Specific Computational Modelling of Articular Cartilage on the Basis of Advanced Multiparametric MRI Techniques.
In: Scientific reports
Nebelung S, Post M, Knobe M, Tingart M, Emans P, Thüring J, Kuhl C, Truhn D,
Detection of Early-Stage Degeneration in Human Articular Cartilage by Multiparametric MR Imaging Mapping of Tissue Functionality.
In: Scientific reports
Ganse B, Böhle F, Pastor T, Gueorguiev B, Altgassen S, Gradl G, Kim BS, Modabber A, Nebelung S, Hildebrand F, Knobe M,
Microcirculation After Trochanteric Femur Fractures: A Prospective Cohort Study Using Non-invasive Laser-Doppler Spectrophotometry.
In: Frontiers in physiology
Jahr H, Gunes S, Kuhn AR, Nebelung S, Pufe T,
Bioreactor-Controlled Physoxia Regulates TGF-β Signaling to Alter Extracellular Matrix Synthesis by Human Chondrocytes.
In: International journal of molecular sciences
Gadermayr M, Li K, Müller M, Truhn D, Krämer N, Merhof D, Gess B,
Domain-specific data augmentation for segmenting MR images of fatty infiltrated human thighs with neural networks.
In: Journal of magnetic resonance imaging : JMRI
Knobe M, Bettag S, Kammerlander C, Altgassen S, Maier KJ, Nebelung S, Prescher A, Horst K, Pishnamaz M, Herren C, Mundt M, Stoffel M, Markert B, Gueorguiev B,
Is bone-cement augmentation of screw-anchor fixation systems superior in unstable femoral neck fractures? A biomechanical cadaveric study.
In: Injury
Truhn D, Schrading S, Haarburger C, Schneider H, Merhof D, Kuhl C,
Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI.
In: Radiology
Gradl-Dietsch G, Hitpaß L, Gueorguiev B, Nebelung S, Schrading S, Knobe M,
Undergraduate Curricular Training in Musculoskeletal Ultrasound by Student Teachers: The Impact of Peyton's Four-Step Approach.
In: Zeitschrift fur Orthopadie und Unfallchirurgie
Michalik R, Pauer T, Brill N, Knobe M, Tingart M, Jahr H, Truhn D, Nebelung S,
Quantitative articular cartilage sub-surface defect assessment using optical coherence tomography: An in-vitro study.
In: Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
Truhn D, Kuhl CK, Ciritsis A, Barabasch A, Kraemer NA,
A New Model for MR Evaluation of Liver Function with Gadoxetic Acid, Including Both Uptake and Excretion.
In: European radiology
Carow JB, Carow J, Gueorguiev B, Klos K, Herren C, Pishnamaz M, Weber CD, Nebelung S, Kim BS, Knobe M,
Soft tissue micro-circulation in the healthy hindfoot: a cross-sectional study with focus on lateral surgical approaches to the calcaneus.
In: International orthopaedics
Klos K, Gueorguiev B, Carow JB, Modabber A, Nebelung S, Kim BS, Horst K, Weber CD, Knobe M,
Soft tissue microcirculation around the healthy Achilles tendon: a cross-sectional study focusing on the Achilles tendon and dorsal surgical approaches to the hindfoot.
In: Journal of orthopaedic surgery and research
Thüring J, Linka K, Itskov M, Knobe M, Hitpaß L, Kuhl C, Truhn D, Nebelung S,
Multiparametric MRI and Computational Modelling in the Assessment of Human Articular Cartilage Properties: A Comprehensive Approach.
In: BioMed research international
Herren C, Reijnen M, Pishnamaz M, Lichte P, Andruszkow H, Nebelung S, Siewe J, Hildebrand F, Kobbe P,
Incidence and Risk Factors for Facet Joint Violation in Open Versus Minimally Invasive Procedures During Pedicle Screw Placement in Patients with Trauma.
In: World neurosurgery
Nebelung S, Sondern B, Jahr H, Tingart M, Knobe M, Thüring J, Kuhl C, Truhn D,
Non-invasive T1ρ mapping of the human cartilage response to loading and unloading.
In: Osteoarthritis and cartilage
Knobe M, Altgassen S, Maier KJ, Gradl-Dietsch G, Kaczmarek C, Nebelung S, Klos K, Kim BS, Gueorguiev B, Horst K, Buecking B,
Screw-blade fixation systems in Pauwels three femoral neck fractures: a biomechanical evaluation.
In: International orthopaedics
Nebelung S, Rath B, Tingart M, Kuhl C, Schrading S,
[Chondral and osteochondral defects : Representation by imaging methods].
In: Der Orthopade
Linka K, Itskov M, Truhn D, Nebelung S, Thüring J,
T2 MR imaging vs. computational modeling of human articular cartilage tissue functionality.
In: Journal of the mechanical behavior of biomedical materials
Kösters AK, Ganse B, Gueorguiev B, Klos K, Modabber A, Nebelung S, Kim BS, Knobe M,
Effects of low-intensity pulsed ultrasound on soft tissue micro-circulation in the foot.
In: International orthopaedics
Kuhl CK, Bruhn R, Krämer N, Nebelung S, Heidenreich A, Schrading S,
Abbreviated Biparametric Prostate MR Imaging in Men with Elevated Prostate-specific Antigen.
In: Radiology
Nebelung S, Post M, Raith S, Fischer H, Knobe M, Braun B, Prescher A, Tingart M, Thüring J, Bruners P, Jahr H, Kuhl C, Truhn D,
Functional in situ assessment of human articular cartilage using MRI: a whole-knee joint loading device.
In: Biomechanics and modeling in mechanobiology
Nebelung S, Sondern B, Oehrl S, Tingart M, Rath B, Pufe T, Raith S, Fischer H, Kuhl C, Jahr H, Truhn D,
Functional MR Imaging Mapping of Human Articular Cartilage Response to Loading.
In: Radiology
Gradl-Dietsch G, Lübke C, Horst K, Simon M, Modabber A, Sönmez TT, Münker R, Nebelung S, Knobe M,
Peyton's four-step approach for teaching complex spinal manipulation techniques - a prospective randomized trial.
In: BMC medical education
Nebelung S, Tingart M, Pufe T, Kuhl C, Jahr H, Truhn D,
Ex vivo quantitative multiparametric MRI mapping of human meniscus degeneration.
In: Skeletal radiology
Ciritsis A, Truhn D, Hansen NL, Otto J, Kuhl CK, Kraemer NA,
Correction: Positive Contrast MRI Techniques for Visualization of Iron-Loaded Hernia Mesh Implants in Patients.
In: PloS one
Arslan E, Nellesen T, Bayer A, Prescher A, Lippross S, Nebelung S, Jahr H, Jaeger C, Huebner WD, Fischer H, Stoffel M, Shakibaei M, Pufe T, Tohidnezhad M,
Effect of platelet mediator concentrate (PMC) on Achilles tenocytes: an in vitro study.
In: BMC musculoskeletal disorders
Brill N, Wirtz M, Merhof D, Tingart M, Jahr H, Truhn D, Schmitt R, Nebelung S,
Polarization-sensitive optical coherence tomography-based imaging, parameterization, and quantification of human cartilage degeneration.
In: Journal of biomedical optics
Ciritsis A, Truhn D, Hansen NL, Otto J, Kuhl CK, Kraemer NA,
Positive Contrast MRI Techniques for Visualization of Iron-Loaded Hernia Mesh Implants in Patients.
In: PloS one
Nebelung S, Brill N, Tingart M, Pufe T, Kuhl C, Jahr H, Truhn D,
Quantitative OCT and MRI biomarkers for the differentiation of cartilage degeneration.
In: Skeletal radiology
Nebelung S, Brill N, Müller F, Tingart M, Pufe T, Merhof D, Schmitt R, Jahr H, Truhn D,
Towards Optical Coherence Tomography-based elastographic evaluation of human cartilage.
In: Journal of the mechanical behavior of biomedical materials
Nebelung W, Reichwein F, Nebelung S,
A simplified arthroscopic bone graft transfer technique in chronic glenoid bone deficiency.
In: Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Jahr H, Brill N, Nebelung S,
Detecting early stage osteoarthritis by optical coherence tomography?
In: Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
Brill N, Riedel J, Schmitt R, Tingart M, Truhn D, Pufe T, Jahr H, Nebelung S,
3D Human cartilage surface characterization by optical coherence tomography.
In: Physics in medicine and biology
Beckmann R, Lippross S, Hartz C, Tohidnezhad M, Ferreira MS, Neuss-Stein S, Seekamp A, Nebelung S, Kweider N, Rath B, Jahr H, Pufe T, Varoga DJ,
Abrasion arthroplasty increases mesenchymal stem cell content of postoperative joint effusions.
In: BMC musculoskeletal disorders
Quack V, Ippendorf AV, Betsch M, Schenker H, Nebelung S, Rath B, Tingart M, Lüring C,
[Multidisciplinary Rehabilitation and Fast-track Rehabilitation after Knee Replacement: Faster, Better, Cheaper? A Survey and Systematic Review of Literature].
In: Die Rehabilitation
de Bont F, Brill N, Schmitt R, Tingart M, Rath B, Pufe T, Jahr H, Nebelung S,
Evaluation of Single-Impact-Induced Cartilage Degeneration by Optical Coherence Tomography.
In: BioMed research international
Brill N, Riedel J, Rath B, Tingart M, Jahr H, Betsch M, Quack V, Pufe T, Schmitt R, Nebelung S,
Optical coherence tomography-based parameterization and quantification of articular cartilage surface integrity.
In: Biomedical optics express
Nebelung S, Brill N, Marx U, Quack V, Tingart M, Schmitt R, Rath B, Jahr H,
Three-dimensional imaging and analysis of human cartilage degeneration using Optical Coherence Tomography.
In: Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Interested in joining the team?
We regularly offer opportunities for Master’s Theses (“Abschlussarbeiten”) as well as doctoral dissertations and PhD projects (“Dr.-Arbeiten” – Dr. med., Dr. rer. medic., Dr.-Ing., Dr. rer. nat.) related to the main research areas of our group.
Our work lies at the interface of medicine, imaging sciences, engineering, natural sciences, and computer science. Research projects cover the development, validation, and clinical implementation of AI methods, advanced image acquisition and post-processing in modalities such as MRI and CT, and the scientific and clinical evaluation of imaging technologies across a wide range of experimental and clinical settings.
We also offer an interdisciplinary environment with medical doctors, clinician scientists, postdoctoral researchers, and PhD candidates, access to state-of-the-art clinical imaging infrastructure, and research questions that emerge directly from clinical practice. Projects can be carried out within our department and in close collaboration with institutes at RWTH Aachen University, ensuring close supervision and regular scientific exchange.
For further information, please contact us directly at AImedicineukaachende.
