A deep learning model to predict dose distributions for breast cancer radiotherapy
This study developed a new deep learning model based on 3D U-Net that can accurately predict dose distributions for breast cancer radiotherapy, which can improve the quality and planning efficiency.
Authors
- Zhikai Liu (ORCID: https://orcid.org/0000-0001-5576-2318)
- Shaobin Wang (ORCID: https://orcid.org/0000-0002-0377-2095)
- Xiaorong Hou (ORCID: https://orcid.org/0000-0002-4903-9489)
- Jing Shen (ORCID: https://orcid.org/0000-0002-4566-5925)
- Yimeng Zhang (ORCID: https://orcid.org/0000-0002-7104-8621)
- Hui Guan (ORCID: https://orcid.org/0000-0003-4377-2644)
- Weishi Cheng
- Lu Bai (ORCID: https://orcid.org/0000-0002-9415-4830)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Vision Technology (United States) (US)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-02-12
- DOI
- https://doi.org/10.1007/s12672-025-01942-4
- Citations
- 1
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.88
Funders
- Peking Union Medical College Hospital