Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model
The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter-reader variability in CTV delineation.
Authors
- Fangxu Xing (ORCID: https://orcid.org/0000-0002-0517-0952)
- Arnaud Beddok (ORCID: https://orcid.org/0000-0002-5512-4161)
- M. Moteabbed
- Yafei Dong (ORCID: https://orcid.org/0000-0001-8354-8001)
- Y.E. Chen
- Laura Rozenblum (ORCID: https://orcid.org/0000-0002-6306-8008)
- Georges El Fakhri (ORCID: https://orcid.org/0000-0002-9005-6993)
- Chao Ma (ORCID: https://orcid.org/0000-0002-2016-8084)
- Thibault Marin (ORCID: https://orcid.org/0000-0002-8669-1003)
- Ruth Lim (ORCID: https://orcid.org/0000-0003-0386-0578)
- Elie Najem
- Xiaofeng Liu (ORCID: https://orcid.org/0000-0002-6506-8933)
- Yue Zhuo (ORCID: https://orcid.org/0000-0002-5739-1896)
- Jonghye Woo (ORCID: https://orcid.org/0000-0002-5621-9218)
- K. S. Grogg (ORCID: https://orcid.org/0000-0002-4649-6377)
Institutions
- Harvard University (US)
- Yale University (US)
- Gordon Center for Medical Imaging (US)
- Massachusetts General Hospital (US)
- Dana-Farber Cancer Institute (US)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-05-03
- DOI
- https://doi.org/10.1002/mp.17865
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Energy
- National Cancer Institute
- National Institute of Biomedical Imaging and Bioengineering