Enhancing automated right‐sided early‐stage breast cancer treatments via deep learning model adaptation without additional training
The proposed technique adapts a DL model initially trained for LSB cancer for right-sided patients. It involves swapping the dose predictions from left to right and adjusting model settings, without the need for additional training. This technique-specific to a TPS-could be transposed to other TPS platforms.
Authors
- Michele Zeverino (ORCID: https://orcid.org/0000-0001-9941-8252)
- Silvia Fabiano
- Raphaël Moeckli (ORCID: https://orcid.org/0000-0002-5885-934X)
- François Bochud (ORCID: https://orcid.org/0000-0003-2076-0296)
- Jean Bourhis (ORCID: https://orcid.org/0000-0001-5162-1171)
- Wendy Jeanneret‐Sozzi (ORCID: https://orcid.org/0000-0002-9661-2428)
Institutions
- University of Zurich (CH)
- University Hospital of Zurich (CH)
- University of Lausanne (CH)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1002/mp.17682
- Citations
- 3
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 5.65