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...

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Detalles Bibliográficos
Autores principales: Wong, Jordan, Huang, Vicky, Wells, Derek, Giambattista, Joshua, Giambattista, Jonathan, Kolbeck, Carter, Otto, Karl, Saibishkumar, Elantholi P., Alexander, Abraham
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
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

Internet

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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