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Automated Quality Assurance of OAR Contouring for Lung Cancer Based on Segmentation With Deep Active Learning
Purpose: Ensuring high-quality data for clinical trials in radiotherapy requires the generation of contours that comply with protocol definitions. The current workflow includes a manual review of the submitted contours, which is time-consuming and subjective. In this study, we developed an automated...
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| Publicado no: | Front Oncol |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7350536/ https://ncbi.nlm.nih.gov/pubmed/32719742 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fonc.2020.00986 |
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