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Evaluation of deep learning-based auto-segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients.
Wang, Zhi; Chang, Yankui; Peng, Zhao; Lv, Yin; Shi, Weijiong; Wang, Fan; Pei, Xi; Xu, X George.
Afiliação
  • Wang Z; Center of Radiological Medical Physics, University of Science and Technology of China, Hefei, China.
  • Chang Y; Department of Radiation Oncology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Peng Z; Center of Radiological Medical Physics, University of Science and Technology of China, Hefei, China.
  • Lv Y; Center of Radiological Medical Physics, University of Science and Technology of China, Hefei, China.
  • Shi W; Department of Radiation Oncology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Wang F; Department of Radiation Oncology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Pei X; Department of Radiation Oncology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Xu XG; Center of Radiological Medical Physics, University of Science and Technology of China, Hefei, China.
J Appl Clin Med Phys ; 21(12): 272-279, 2020 Dec.
Article em En | MEDLINE | ID: mdl-33238060

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias do Colo do Útero / Aprendizado Profundo Tipo de estudo: Etiology_studies / Guideline / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias do Colo do Útero / Aprendizado Profundo Tipo de estudo: Etiology_studies / Guideline / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article