Fluence Map Prediction Using Deep Learning Models – Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy
2020 · Frontiers in Artificial Intelligence · 57 citations
https://doi.org/10.3389/frai.2020.00068
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Yang Sheng
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Yang Sheng is an academic researcher from Zhejiang Chinese Medical University. The author has contributed to research in topics: Advanced Radiotherapy Techniques & Radiomics and Machine Learning in Medical Imaging & Medical Imaging Techniques and Applications. The author has an h-index of 17, co-authored 80 publications.
ORCID: 0000-0003-3380-1966Papers by this author
worksAn Interpretable Planning Bot for Pancreas Stereotactic Body Radiation Therapy
2020 · International Journal of Radiation Oncology*Biology*Physics · 39 citations
https://doi.org/10.1016/j.ijrobp.2020.10.019
Deep Learning–Based Fluence Map Prediction for Pancreas Stereotactic Body Radiation Therapy With Simultaneous Integrated Boost
2021 · Advances in Radiation Oncology · 26 citations
https://doi.org/10.1016/j.adro.2021.100672
A reinforcement learning agent for head and neck intensity-modulated radiation therapy
2024 · Frontiers in Physics · 5 citations
https://doi.org/10.3389/fphy.2024.1331849
Clinical commissioning and introduction of an in‐house artificial intelligence (AI) platform for automated head and neck intensity modulated radiation therapy (IMRT) treatment planning
2024 · Journal of Applied Clinical Medical Physics · 3 citations
https://doi.org/10.1002/acm2.14558
Training a Diffusion-GAN to Improve the Head-and-Neck Intensity Modulated Radiation Therapy Fluence Generator
2024 · International Journal of Radiation Oncology*Biology*Physics · 0 citations
https://doi.org/10.1016/j.ijrobp.2024.07.406
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