Evaluation of deep learning-based target auto-segmentation for Magnetic Resonance Imaging-guided cervix brachytherapy
Auto-segmentation introduces a bias in the manual delineations but this bias is clinically irrelevant. Auto-segmentation, particularly patient-specific fine-tuning, is a time-saving tool that can improve treatment logistics and therefore reduce patient burden during the second fraction of cervix brachytherapy.
Authors
- Sandra van der Velden (ORCID: https://orcid.org/0000-0002-8054-0175)
- E.C. Rijkmans (ORCID: https://orcid.org/0000-0003-0011-9805)
- Tomas Janssen (ORCID: https://orcid.org/0000-0003-2807-8670)
- Rita Simões (ORCID: https://orcid.org/0000-0002-4976-3557)
- Eva E. Schaake
- Marlies E. Nowee
Institutions
- The Netherlands Cancer Institute (NL)
Publication Details
- Journal
- Physics and Imaging in Radiation Oncology
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1016/j.phro.2024.100669
- Citations
- 2
- Primary Topic
- Endometrial and Cervical Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.17