Endorsed projects

EFOMP as a Stakeholder (2022-2026)

TraMeXI (Traceability in Medical X-ray Imaging dosimetry)


X-ray imaging is an important technique used in medicine however it’s use forms the largest component of exposure to artificial ionizing radiation. Consistent quantification of a patient’s exposure to radiation with calibrated dosimetry equipment is essential to comply with Council Directive and ensure patient safety. Currently, the procedures used by calibration laboratories, based on relevant standards and international protocols, do not fully consider the recent technical developments in X-ray imaging. This project will perform a critical assessment of conditions applied in calibrations and study the performance of different dosimeters. Updated measurement and calibration procedures will be proposed for inclusion into standards and protocols.

The project team is running two surveys for medical physicists to collect data on currently used dosimeters and radiation qualities. Now you have a chance to impact, so please reply to the survey by the end of November: 



Real-Time Adaptive Particle Therapy Of Cancer (RAPTOR) Real-Time Adaptive Particle Therapy Of Cancer (RAPTOR)


The high precision of PT comes as a double-edged sword since PT is normally less robust than X-ray radiotherapy. Several uncertainties, such as changes in anatomy, positioning, organ delineation and systematic uncertainties can have a significant impact on where the final dose is delivered. The reliability of PT has increased in recent years with robust treatment planning, however, it still remains sensitive to larger uncertainties that have to be minimized to exploit the full benefit of PT. The clinical workflow in PT has been adopted from conventional X-ray radiotherapy, where the treatment plan is based on the initial computed tomography (CT) scan of a patient. Since, the treatment usually lasts several weeks, it is likely that the initial treatment plan becomes less valid due to the changes of the patient anatomy as the treatment progresses.




AI-POD project is funded by the European Commission under Horizon Europe. The project commenced on May 1, 2023, and is scheduled to run until April 30, 2027. Led by Prof. Ulrike Attenberger from the University Hospital Bonn (UKB), Germany, the consortium comprises 11 partners from 8 European countries.

AI-POD is a transformative initiative set out to revolutionise obesity-related disease prediction for cardiovascular disease. The mission of AI-POD is to significantly improve the risk assessment and management of obesity-related vascular disease. This is achieved through developing a unique AI-based risk prediction score and Clinical Decision Support System, both guided by a wealth of individual patient data. Furthermore, the aim of the project is to develop a Citizen App that integrates real-time monitoring of diet and lifestyle into standard risk assessment, forming a fully digitalized feedback loop between patients and clinicians. Through these innovative tools, a digital feedback loop between patients and clinicians will be created. Ultimately  transform the standard of care for obesity-related diseases, potentially shaping future treatment strategies and guidelines.