Total brain dose estimation in single‐isocenter‐multiple‐targets (SIMT) radiosurgery via a novel deep neural network with spherical convolutions
The deep learning model provides treatment planners with accurate prediction of dose to normal brain, enabling improved consistency in treatment planning quality. This method can be extended to other brain-related analyses as an efficient data dimension reduction method.
Authors
- Chunhao Wang (ORCID: https://orcid.org/0000-0002-6945-7119)
- Trey C. Mullikin (ORCID: https://orcid.org/0000-0002-1099-1763)
- Zhenyu Yang (ORCID: https://orcid.org/0000-0002-7137-2552)
- Eugene Vaios (ORCID: https://orcid.org/0000-0003-2122-6650)
- Mercedeh Khazaieli
- F Yin (ORCID: https://orcid.org/0000-0002-2025-4740)
- Jingtong Zhao (ORCID: https://orcid.org/0000-0003-2717-4847)
- Rihui Zhang
- Albert Yang
Institutions
- Duke University (US)
- Duke Kunshan University (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1002/mp.17748
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00