Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy
Patient-specific fine-tuning of automatically segmented rectal tumors, using images and segmentations from all previous fractions, yields superior quality compared to other auto-segmentation approaches.
Authors
- Doenja M. J. Lambregts (ORCID: https://orcid.org/0000-0003-2990-0099)
- Corrie A.M. Marijnen (ORCID: https://orcid.org/0000-0003-0189-5953)
- Femke P. Peters (ORCID: https://orcid.org/0000-0001-9085-447X)
- Tomas Janssen (ORCID: https://orcid.org/0000-0003-2807-8670)
- Chavelli M. Kensen (ORCID: https://orcid.org/0000-0001-9161-6852)
- Rita Simões (ORCID: https://orcid.org/0000-0002-4976-3557)
- Anja Betgen
- Uulke A van der Heide
- Lisa Wiersema
Institutions
- The Netherlands Cancer Institute (NL)
Publication Details
- Journal
- Physics and Imaging in Radiation Oncology
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1016/j.phro.2024.100648
- Citations
- 6
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.65