Evaluation Exploration of Atlas-Based and Deep Learning-Based Automatic Contouring for Nasopharyngeal Carcinoma.

Wang, Jinyuan; Chen, Zhaocai; Yang, Cungeng; Qu, Baolin; Ma, Lin; Fan, Wenjun; Zhou, Qichao; Zheng, Qingzeng; Xu, Shouping

Wang, Jinyuan; Chen, Zhaocai; Yang, Cungeng; Qu, Baolin; Ma, Lin; Fan, Wenjun; Zhou, Qichao; Zheng, Qingzeng; Xu, Shouping.

Afiliação

Wang J; Department of Radiation Oncology, The First Medical Center of the Chinese PLA General Hospital, Beijing, China.
Chen Z; Manteia Technologies Co., Ltd., Xiamen, China.
Yang C; Manteia Technologies Co., Ltd., Xiamen, China.
Qu B; Department of Radiation Oncology, The First Medical Center of the Chinese PLA General Hospital, Beijing, China.
Ma L; Department of Radiation Oncology, The First Medical Center of the Chinese PLA General Hospital, Beijing, China.
Fan W; Department of Radiation Oncology, The First Medical Center of the Chinese PLA General Hospital, Beijing, China.
Zhou Q; Manteia Technologies Co., Ltd., Xiamen, China.
Zheng Q; Department of Radiation Oncology, Beijing Geriatric Hospital, Beijing, China.
Xu S; Department of Radiation Oncology, The First Medical Center of the Chinese PLA General Hospital, Beijing, China.

Front Oncol ; 12: 833816, 2022.

Article em En | MEDLINE | ID: mdl-35433460

Palavras-chave

atlas; auto-segmentation; deep learning (DL); nasopharyngeal carcinoma (NPC); organs at risk (OARs); training

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Front Oncol Ano de publicação: 2022 Tipo de documento: Article

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