Patient-Specific Deep Learning Tracking Framework for Real-Time 2D Target Localization in Magnetic Resonance Imaging-Guided Radiation Therapy
For targets in the thorax, abdomen, and pelvis, we found 2 PS DL models to provide accurate real-time target localization during MRI-guided radiotherapy.
Authors
- Sebastian Marschner (ORCID: https://orcid.org/0000-0002-8121-358X)
- Stefanie Corradini
- Claus Belka (ORCID: https://orcid.org/0000-0002-1287-7825)
- Michael Reiner
- Cristina I. Papadopoulou
- Christopher Kurz
- Marco Riboldi (ORCID: https://orcid.org/0000-0002-2431-4966)
- Moritz Rabe (ORCID: https://orcid.org/0000-0002-7085-4066)
- Guillaume Landry (ORCID: https://orcid.org/0000-0003-1707-4068)
- Laura Velezmoro
- Elia Lombardo (ORCID: https://orcid.org/0000-0003-4522-8298)
- Zhuojie Sui (ORCID: https://orcid.org/0000-0002-0841-6073)
- Claudia Tejero
Institutions
- LMU Klinikum (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- International Journal of Radiation Oncology*Biology*Physics
- Published
- 2024-10-24
- DOI
- https://doi.org/10.1016/j.ijrobp.2024.10.021
- Citations
- 11
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 6.68
Funders
- Deutsche Forschungsgemeinschaft