Pro-active risk analysis of an in-house developed deep learning based autoplanning tool for breast Volumetric Modulated Arc Therapy
The pro-active risk analysis revealed possible risks in the implemented workflow and led to the implementation of mitigation strategies that decreased the risk scores for safer clinical use.
Authors
- Aline Van der Vorst (ORCID: https://orcid.org/0009-0006-4983-5609)
- Laurence Delombaerde (ORCID: https://orcid.org/0000-0001-6478-4105)
- Truus Reynders
- Chahrazad Benazzouz
- Wouter Crijns (ORCID: https://orcid.org/0000-0002-2894-3110)
- Caroline Weltens (ORCID: https://orcid.org/0000-0001-7790-7151)
- Liesbeth Vandewinckele (ORCID: https://orcid.org/0000-0002-7375-196X)
- Dylan Callens (ORCID: https://orcid.org/0000-0003-2348-9868)
- Jan Verstraete (ORCID: https://orcid.org/0000-0003-4536-5639)
- L. Pape
- Adinda Baeten
Institutions
- Universitair Ziekenhuis Leuven (BE)
- KU Leuven (BE)
Publication Details
- Journal
- Physics and Imaging in Radiation Oncology
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1016/j.phro.2024.100677
- Citations
- 2
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.22
Funders
- Fonds Wetenschappelijk Onderzoek
- Vlaamse regering
- Universitaire Ziekenhuizen Leuven, KU Leuven