[Automatic Post-operative Cervical Cancer Target Area and Organ at Risk Outlining Based on Fusion Convolutional Neural Network].

Zhou, Jin; Yang, Wei; Gu, Shanshan; Quan, Hong; Liu, Jie; Ju, Zhongjian

Zhou, Jin; Yang, Wei; Gu, Shanshan; Quan, Hong; Liu, Jie; Ju, Zhongjian.

Afiliação

Zhou J; School of Physics Science and Technology, Wuhan University, Wuhan, 430072.
Yang W; Radiotherapy Department, First Medical Center, General Hospital of Chinese People's Liberation Army, Beijing, 100853.
Gu S; Radiotherapy Department, First Medical Center, General Hospital of Chinese People's Liberation Army, Beijing, 100853.
Quan H; School of Physics Science and Technology, Wuhan University, Wuhan, 430072.
Liu J; Beijing Eastraycloud Technology Inc., Beijing, 100020.
Ju Z; Radiotherapy Department, First Medical Center, General Hospital of Chinese People's Liberation Army, Beijing, 100853.

Zhongguo Yi Liao Qi Xie Za Zhi ; 46(2): 132-136, 2022 Mar 30.

Article em Zh | MEDLINE | ID: mdl-35411736

Assuntos

Neoplasias do Colo do Útero; Feminino; Humanos; Processamento de Imagem Assistida por Computador; Redes Neurais de Computação; Órgãos em Risco; Pelve; Tomografia Computadorizada por Raios X; Neoplasias do Colo do Útero/diagnóstico por imagem; Neoplasias do Colo do Útero/cirurgia

Palavras-chave

automatic outline; cervical cancer; deep learning; fusion neural network; radiotherapy

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias do Colo do Útero Tipo de estudo: Etiology_studies / Risk_factors_studies Limite: Female / Humans Idioma: Zh Revista: Zhongguo Yi Liao Qi Xie Za Zhi Ano de publicação: 2022 Tipo de documento: Article

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