Translational imaging
In recent years, medicine has seen remarkable advances that have fundamentally changed the treatment of numerous diseases and significantly improved the prognosis of many patients. The development towards increasingly personalized precision medicine is evident in almost all medical disciplines. In this context, radiology has developed into a key interdisciplinary discipline that enables precise diagnostics, progress monitoring and sound clinical decision-making.
In this important role, conventional imaging procedures and established workflows in radiology are increasingly reaching their limits: increasing numbers of examinations, growing data volumes and the increasing need for complex image interpretation in a clinical context pose considerable challenges. In recent years, numerous studies have demonstrated various technological solutions to these problems - yet for many of them there is a relevant translational gap between methodological innovation and clinical application.
The aim of the working group is therefore to investigate innovative technologies in radiology with high translational potential. This includes scanner-based approaches such as spectral and photon-counting CT as well as artificial intelligence applications such as foundation models or computer vision-based AI tools. The clear focus is on methodological validation and thus the improved clinical applicability of these technologies. A particular focus is on oncological imaging.
Current projects and cooperations
Current projects
- Imaging biomarkers for AI-based therapy response prediction in patients under immune checkpoint inhibition
- Multiparametric spectral CT-based characterization of liver lesions
- Open Medical Inference (OMI)
- Use of foundation models in oncological imaging workflows
Collaborations
- Data Science Group, Institute for Diagnostic and Interventional Radiology
- Center for Integrated Oncology (CIO Cologne)
- Institute for Medical Informatics, University of Cologne (BIK)