As reported in public INT staff profiles.
AI-driven radiotherapy planning
RAPID Solution
Optimizing radiotherapy planning through an AI-driven solution for breath-hold selection in breast cancer.
Scientific Aim
RAPID Solution focuses on a practical radiotherapy planning problem in breast cancer: deciding when deep inspiration breath hold is likely to provide a relevant dosimetric and clinical advantage.
The project combines imaging, respiratory tracking, synthetic CT datasets, and deep learning to build a decision support workflow that can guide patient selection during the planning phase.
The expected output is an interpretable AI-assisted tool that helps reduce cardiac exposure and supports efficient, personalized radiotherapy planning.
Scientific Contributions
Conference abstracts, papers, protocol records, and outputs associated with the project.
Abstracts
To be updated when conference abstracts become public.
Papers / outputs
Project outputs and manuscripts to be updated after public release or publication.
Items marked as to be confirmed should be replaced when the final bibliographic record, DOI, or author list is available.
