An Adversarial Deep-Learning-Based Model for Cervical Cancer CTV Segmentation With Multicenter Blinded Randomized Controlled Validation

PURPOSE: To propose a novel deep-learning-based auto-segmentation model for CTV delineation in cervical cancer and to evaluate whether it can perform comparably well to manual delineation by a three-stage multicenter evaluation framework. METHODS: An adversarial deep-learning-based auto-segmentation...

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Detalles Bibliográficos
Autores principales: Liu, Zhikai, Chen, Wanqi, Guan, Hui, Zhen, Hongnan, Shen, Jing, Liu, Xia, Liu, An, Li, Richard, Geng, Jianhao, You, Jing, Wang, Weihu, Li, Zhouyu, Zhang, Yongfeng, Chen, Yuanyuan, Du, Junjie, Chen, Qi, Chen, Yu, Wang, Shaobin, Zhang, Fuquan, Qiu, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417437/
https://www.ncbi.nlm.nih.gov/pubmed/34490103
http://dx.doi.org/10.3389/fonc.2021.702270

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417437/
https://www.ncbi.nlm.nih.gov/pubmed/34490103
http://dx.doi.org/10.3389/fonc.2021.702270

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