Monte Carlo-based simulation of virtual 3 and 4-dimensional cone-beam computed tomography from computed tomography images: An end-to-end framework and a deep learning-based speedup strategy
The presented MC pipeline and speedup approach provide an openly accessible end-to-end framework for researchers and clinicians to investigate limitations of image-guided radiation therapy workflows built on both (4D) CT and CBCT images.
Authors
- René Werner (ORCID: https://orcid.org/0000-0002-2296-3305)
- Frederic Madesta (ORCID: https://orcid.org/0000-0001-8987-7690)
- Tobias Gauer
- Rüdiger Schmitz (ORCID: https://orcid.org/0000-0002-2414-9817)
- Thilo Sentker (ORCID: https://orcid.org/0000-0001-6663-0003)
- Clemens Rohling
Institutions
- Universität Hamburg (DE)
- University Medical Center Hamburg-Eppendorf (DE)
Publication Details
- Journal
- Physics and Imaging in Radiation Oncology
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1016/j.phro.2024.100644
- Citations
- 3
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- Deutsche Forschungsgemeinschaft
- Siemens Healthineers
- Universitätsklinikum Hamburg-Eppendorf