Technical University of Munich – Klinikum rechts der Isar

The university hospital of the Technical University of Munich,  Klinikum rechts der Isar, is now among the 20 best hospitals in the world (Newsweek 2023). Patients at Klinikum rechts der Isar benefit from cutting-edge research in areas such as cancer research, neurology, immune research and cardiology. In addition, the hospital and the Department of Medicine cooperate closely with TUM’s other fields of research. This results in numerous advantages for research, teaching and patient care. For example, at TranslaTUM, the Center for Translational Cancer Research, researchers from medicine, engineering and the natural sciences work together to find new approaches to cancer treatment and bring them into application as quickly as possible. As an interdisciplinary research institute, the Munich Institute for Biomedical Engineering (MIBE) brings together researchers from almost all TUM Schools to develop methods for the prevention, diagnosis and treatment of diseases. In the future, new approaches in the fields of data science and artificial intelligence in medicine will be developed at the Center for Digital Medicine and Health and brought into clinical application.

Role of institution in the project

TUM-MRI will lead the development of privacy-preserving federated learning for medical images (Task 6.3).

Prof. Dr. Daniel Rückert

Professor Rückert’s field of research is the area of Artificial Intelligence (AI) and Machine Learning and their application to medicine and healthcare. His research focuses on (1) the development of innovative algorithms for biomedical image acquisition, image analysis and image interpretation – especially in the areas of image reconstruction, registration, segmentation, traching and modelling; (2) AI for extracting clinically useful information from biomedical images – especially for computer-assisted diagnosis and prognosis. Since 2020, Daniel Rückert is Alexander von Humboldt Professor for AI in Medicine and Healthcare at the Technical University of Munich. He is also a Professor at Imperial College London. He gained a MSc from Technical University Berlin in 1993, a PhD from Imperial College in 1997, followed by a post-doc at King’s College London. In 1999 he joined Imperial College as a Lecturer, becoming Senior Lecturer in 2003 and full Professor in 2005. From 2016 to 2020 he served as Head of the Department of Computing at Imperial College.

Georg Kaissis

Georg Kaissis is an adjunct assistant professor at TUM, where he leads the Privacy-Preserving and Trustworthy Artificial Intelligence research group at the Institute for Artificial Intelligence in Medicine. He also lead the Reliable AI research group at Helmholtz Zentrum Munich. He obtained his medical degree from LMU Munich, Master's Degree in Health Business Administration from FAU Nuremberg and a specialist diagnostic radiologist board certification at the Institute for Diagnostic and Interventional Radiology at TUM, where he serves as a consultant radiologist. He did his post-doc in Artificial Intelligence at the Department of Computing at Imperial College London. His research focuses on privacy-preserving AI and in particular Differential Privacy and its applications to medical deep learning.

Join the EUCAIM Consortium

Open Call for New Beneficiaries

We’re inviting new partners to enhance our pan-European infrastructure for cancer images and artificial intelligence.

Whether you’re a data holder with valuable cancer images or an innovator developing AI tools for precision medicine, this is your chance to contribute to a groundbreaking project.

Apply by 10 June 2024!

Open Call Webinar

We recently hosted a webinar with more details for prospective applicants to the open call. A recording is available.

Our open Call for new collaborators
launches in April 2024

Opportunities for data holders & AI developers to contribute await! Let‘s join forces to enhance cancer diagnosis and treatment

Be the first to know and apply!

March 14, 10:00-11:30 aM CET



Explore the potential for AI-driven cancer care advancements!
Learn how to access and utilize our federated cancer image repository. The webinar is for AI Innovators & Data Providers interested in the platform and will feature an introduction to EUCAIM & Cancer Image Europe and a demonstration of data exploration & access.

Survey Invitation

Join Leading Experts In Shaping AI In Cancer

EUCAIM is looking for your feedback! We have recently published a Stakeholder Survey in order to reach out to potential end-users and stakeholders. We believe that your insights could significantly contribute to understanding the expectations of potential users and identifying the essential aspects that stakeholders find crucial for future engagement and collaboration with the platform.

Therefore, we would like to invite you to participate in the Stakeholder Survey about the Cancer Image Europe platform.

Completing the survey will take approximately 10 minutes. Your participation is crucial to the success of this project, and we deeply appreciate your expertise in shaping the future of cancer imaging and treatment.