Convolutional neural networks for the automated segmentation of malignant pleural mesothelioma: analysis of performance based on probability map threshold (Alliance)
- Citation:
- Med Phys vol 49 (6 ) pp e680-e681
- Meeting Instance:
- AAPM 2022
- Year:
- 2022
- Type:
- Abstract
- Sub type:
- ePoster
- Funding:
- NCTN
- Endpoint:
- Secondary-not-in-original
- Analysis:
- Primary
- Data Sharing:
- No-Data-Sharing
- Status:
- Presented/Published
- Citation Status:
- epub-ppub
- Note:
- Methodological:
- No
- Biospecimen:
- No
- SDC:
- No
- Parents:
- None
- Children:
- 3822
- Program:
- OGC
- Primary Committee:
- Respiratory
- Sec. Committees:
- Pharmas:
- Grants:
- U10CA180821, U10CA180882
- Corr. Author:
- Authors:
- Mena Shenouda Eyjólfur Guðmundsson Feng Li Christopher Straus Hedy L. Kindler Arkadiusz Z. Dudek Thomas E. Stinchcombe Xiaofei Wang Adam Starkey Samuel G. Armato III
- Networks:
- LAPS-IL057, LAPS-MN026, LAPS-NC010
- Study
- CALGB-30901
- Multiple Studies, or Legacy Studies in Alliance Study:
- Phases:
- 2
- Keywords:
- CNNs, probability maps, CT, thresholds, MPM, tumor volume