1 citations · 1 across the 7 of their papers we have counts for
7 papers
Learning to Optimize Radiotherapy Plans via Fluence Maps Diffusion Model Generation and LSTM-based Optimization
Isabella Poles, Simon Arberet, Riqiang Gao +5
Volumetric Modulated Arc Therapy (VMAT) is a cornerstone of modern radiation therapy, enabling highly conformal tumor irradiation and healthy-tissue sparing. Yet, its planning solv…
Any2Any 3D Diffusion Models with Knowledge Transfer: A Radiotherapy Planning Study
Yuhan Wang, Zihan Li, Han Liu +7
Voxel-wise dose prediction is a critical yet challenging task in practical radiotherapy (RT) planning, as bespoke models trained from scratch often struggle to generalize across di…
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 +6
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…
Automating RT Planning at Scale: High Quality Data For AI Training
Riqiang Gao, Mamadou Diallo, Han Liu +10
Radiotherapy (RT) planning is complex, subjective, and time-intensive. Advances with artificial intelligence (AI) promise to improve its precision and efficiency, but progress is o…
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin C. Ghesu, Simon Arberet +5
In contemporary radiotherapy planning (RTP), a key module leaf sequencing is predominantly addressed by optimization-based approaches. In this paper, we propose a novel deep reinfo…