149 citations · 186 across the 10 of their papers we have counts for
6 papers · 1 filter
AI in Proton Therapy Treatment Planning: A Review
Yuzhen Ding, Hongying Feng, Martin Bues +12
Purpose: Proton therapy provides superior dose conformity compared to photon therapy, but its treatment planning is challenged by sensitivity to anatomical changes, setup/range unc…
Diffusion Transformer-based Universal Dose Denoising for Pencil Beam Scanning Proton Therapy
Yuzhen Ding, Jason Holmes, Hongying Feng +13
Purpose: Intensity-modulated proton therapy (IMPT) offers precise tumor coverage while sparing organs at risk (OARs) in head and neck (H&N) cancer. However, its sensitivity to anat…
Artificial Intelligence-Facilitated Online Adaptive Proton Therapy Using Pencil Beam Scanning Proton Therapy
Hongying Feng, Jie Shan, Carlos E. Vargas +10
We propose an oAPT workflow that incorporates all these functionalities and validate its clinical implementation feasibility with prostate patients. AI-based auto-segmentation tool…
Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 report
Jason Holmes, Lian Zhang, Yuzhen Ding +7
Purpose: To introduce the concept of using large language models (LLMs) to re-label structure names in accordance with the American Association of Physicists in Medicine (AAPM) Tas…
Artificial General Intelligence for Radiation Oncology
Chenbin Liu, Zhengliang Liu, Jason Holmes +14
The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can…
Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics
Jason Holmes, Zhengliang Liu, Lian Zhang +8
We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have…