DDM Joins EU-Funded Doctoral Programmes Advancing AI in Healthcare

The Department of Digital Medicine (DDM) is set to play a key role in a major European research initiative advancing artificial intelligence in cancer treatment.

The MSCA will support 141 doctoral programmes to train and develop the skills of around 2115 doctoral candidates
The MSCA will support 141 doctoral programmes to train and develop the skills of around 2115 doctoral candidates. Image credits: MSCA

 

DDM Professor Mauricio Reyes and his research group at the ARTORG Center for Biomedical Engineering Research, University of Bern, will contribute to the newly funded project TTRAIL (Trustworthy Transferable Radiotherapy with Artificial Intelligence), which has been selected under the latest Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks call. The programme is part of a €617 million investment by the European Union to support cutting-edge doctoral training across Europe.

TTRAIL aims to train 15 doctoral researchers, referred to as “AIRTISTs”, to become the next generation of translational AI scientists in radiotherapy. The project focuses on developing trustworthy and transferable AI systems that can be integrated into clinical practice.

Within this initiative, Prof. Reyes’s group will lead the development of next-generation explainable AI systems for radiation therapy. Their work will also establish clinically relevant training paradigms for AI-driven autocontouring, an essential process in radiotherapy planning that defines tumour and organ boundaries.

The project is led by Principal Investigator Oscar Acosta and coordinated by Université de Rennes and the Laboratoire Traitement du Signal et de l’Image (LTSI). It brings together an extensive international consortium of academic institutions, industry leaders, and clinical partners.

Academic collaborators include institutions such as The University of Manchester, Karlsruhe Institute of Technology, and Politecnico di Milano, among others. Industry partners include Siemens Healthineers, Brainlab, and Dassault Systèmes, ensuring strong links between research, technology development, and clinical application.

Clinical partners across Europe will further support the programme by providing real-world healthcare environments for testing and validation.

Being part of TTRAIL allows our lab to push the boundaries of explainable AI in radiotherapy. Training the next generation of AI scientists in a clinical context is an exciting opportunity to make cancer treatments safer and more precise.”, says DDM Prof. Mauricio Reyes.
 

The selection of TTRAIL highlights the growing importance of interdisciplinary collaboration in tackling complex healthcare challenges. For the Department of Digital Medicine, participation in this prestigious MSCA Doctoral Network reinforces its position at the forefront of AI-driven medical innovation.

With the project now officially funded, the consortium is preparing to begin its work on shaping the future of AI in radiotherapy, aiming to make treatments more precise, transparent, and clinically effective.

Learn more about the MSCA Doctoral Network call here.

Principal Investigators:

Oscar Acosta, Université de Rennes, France | Javier Pascau, Universidad Carlos III de Madrid, Spain | Eliana Vasquez Osorio, The University of Manchester, UK | Mauricio Reyes, University of Bern, Switzerland | Maria Francesca Spadea, Karlsruhe Institute of Technology, Germany | Diana Mateus, Ecole Centrale Nantes, France | Maria A. Zuluaga, Vincent Jaouen, EURECOM, France | Tiziana Rancati, IRCCS, Italy | Norberto Malpica, Rey Juan Carlos University, Spain | George Kagadis, University of Patras, Greece | Eugenia Mylona, University of Patras, Greece | Anaïs Barateau, Université de Rennes, France | Gloria Diaz, Paolo Zunino, Politecnico di Milano, Italy.

The Medical Image Analysis (MIA) group

Led by DDM Prof. Mauricio Reyes, The Medical Image Analysis (MIA) group at the ARTORG Center for Biomedical Engineering Research develops advanced AI-based image analysis technologies and translational biomedical engineering solutions to quantify, diagnose, and monitor diseases. The core expertise of the department lies in multimodal image segmentation and longitudinal analysis for brain tumours (glioblastoma, brain metastases, ischemic stroke), as well as deep learning for thoracic imaging. The focus is on identifying robust, non-invasive imaging biomarkers to characterize disease evolution, guide therapy, and support clinical decision-making.