4 papers
AI End-to-End Radiation Treatment Planning Under One Second
Simon Arberet, Riqiang Gao, Martin Kraus +9
Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning time and inter-planner variability, improving efficiency and consistency in clini…
Demo: Generative AI helps Radiotherapy Planning with User Preference
Riqiang Gao, Simon Arberet, Martin Kraus +5
Radiotherapy planning is a highly complex process that often varies significantly across institutions and individual planners. Most existing deep learning approaches for 3D dose pr…
A Beam's Eye View to Fluence Maps 3D Network for Ultra Fast VMAT Radiotherapy Planning
Simon Arberet, Florin C. Ghesu, Riqiang Gao +4
Volumetric Modulated Arc Therapy (VMAT) revolutionizes cancer treatment by precisely delivering radiation while sparing healthy tissues. Fluence maps generation, crucial in VMAT pl…
Towards Integrating Epistemic Uncertainty Estimation into the Radiotherapy Workflow
Marvin Tom Teichmann, Manasi Datar, Lisa Kratzke +2
The precision of contouring target structures and organs-at-risk (OAR) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Recent advancements i…