Uncertainty-guided pancreatic tumor auto-segmentation with Tversky ensemble
Our study demonstrated the effectiveness of employing an ensemble-based uncertainty estimation technique for pancreatic tumor segmentation. The approach provided clinicians with a consensus probability map that could be fine-tuned in line with their preferences, generating contours with greater confidence.
Authors
- Rachael Martin (ORCID: https://orcid.org/0000-0002-3866-6823)
- Dong Joo Rhee (ORCID: https://orcid.org/0000-0003-0486-1556)
- Ethan B. Ludmir (ORCID: https://orcid.org/0000-0002-5472-5344)
- Xinru Chen (ORCID: https://orcid.org/0000-0002-9989-8943)
- Aashish C. Gupta (ORCID: https://orcid.org/0000-0002-0178-0921)
- Carlos E. Cardenas (ORCID: https://orcid.org/0000-0003-1414-3849)
- Laurence E. Court (ORCID: https://orcid.org/0000-0002-3241-6145)
- Jack Duryea (ORCID: https://orcid.org/0000-0002-5539-5885)
- Yao Zhao (ORCID: https://orcid.org/0000-0001-8863-841X)
- Skylar Gay (ORCID: https://orcid.org/0000-0003-4659-0766)
- Jinzhong Yang (ORCID: https://orcid.org/0000-0002-9254-4501)
- Albert C. Koong (ORCID: https://orcid.org/0000-0001-9824-1643)
- Cenji Yu (ORCID: https://orcid.org/0000-0002-4350-9910)
- Tucker Netherton (ORCID: https://orcid.org/0000-0003-1583-7121)
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- University of Alabama at Birmingham (US)
Publication Details
- Journal
- Physics and Imaging in Radiation Oncology
- Published
- 2025-03-08
- DOI
- https://doi.org/10.1016/j.phro.2025.100740
- Citations
- 1
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.84