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Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers
PURPOSE: We recently described the validation of deep learning-based auto-segmented contour (DC) models for organs at risk (OAR) and clinical target volumes (CTV). In this study, we evaluate the performance of implemented DC models in the clinical radiotherapy (RT) planning workflow and report on us...
Autores principales: | Wong, Jordan, Huang, Vicky, Wells, Derek, Giambattista, Joshua, Giambattista, Jonathan, Kolbeck, Carter, Otto, Karl, Saibishkumar, Elantholi P., Alexander, Abraham |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8186196/ https://www.ncbi.nlm.nih.gov/pubmed/34103062 http://dx.doi.org/10.1186/s13014-021-01831-4 |
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