Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers

Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers

Abstract 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 repo...

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Bibliographic Details
Main Authors: Jordan Wong, Vicky Huang, Derek Wells, Joshua Giambattista, Jonathan Giambattista, Carter Kolbeck, Karl Otto, Elantholi P. Saibishkumar, Abraham Alexander
Format: Article
Language:English
Published: BMC 2021-06-01
Series:Radiation Oncology
Subjects:
Machine learning
Radiotherapy
Radiotherapy planning
Computer-assisted
Online Access:https://doi.org/10.1186/s13014-021-01831-4

Internet

https://doi.org/10.1186/s13014-021-01831-4

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