Enhancing CBCT‐based CT synthesis using planning MRI in adaptive proton therapy for head cancer: A deep learning approach
We demonstrated the promising contribution of MRI to CBCT-based CT synthesis, enhancing sCT image quality and dose calculation accuracy. Future efforts should aim to collect a larger dataset and validate the integration of MRI in APT.
Authors
- Juan Manuel Molina‐Maza (ORCID: https://orcid.org/0009-0007-7137-2572)
- Ángel Torrado-Carvajal (ORCID: https://orcid.org/0000-0002-1540-2809)
- Juan María Pérez-Moreno (ORCID: https://orcid.org/0000-0001-6271-1842)
- Norberto Malpica (ORCID: https://orcid.org/0000-0003-4618-7459)
- Borja Rodríguez-Vila (ORCID: https://orcid.org/0000-0003-4779-0225)
- A. Mazal (ORCID: https://orcid.org/0000-0003-1391-8446)
- Juan Antonio Vera‐Sánchez (ORCID: https://orcid.org/0000-0002-3594-9457)
- David Viar‐Hernandez (ORCID: https://orcid.org/0000-0002-1938-2980)
- Blanca Rodriguez-Gonzalez (ORCID: https://orcid.org/0009-0007-0982-1293)
- Javier Sequeiro-Gonzalez
Institutions
- Universidad Rey Juan Carlos (ES)
- Hospital Universitario Quirónsalud Madrid (ES)
Publication Details
- Journal
- Journal of Applied Clinical Medical Physics
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/acm2.70367
- Primary Topic
- Radiation Therapy and Dosimetry
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Comunidad de Madrid
- Universidad Rey Juan Carlos