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Using the apparent diffusion coefficient histogram analysis to predict response to neoadjuvant chemotherapy in patients with breast cancer: comparison among three region of interest selection methods.
Geng, Xiaochuan; Zhang, Dandan; Suo, Shiteng; Chen, Jie; Cheng, Fang; Zhang, Kebei; Zhang, Qing; Li, Lan; Lu, Yang; Hua, Jia; Zhuang, Zhiguo.
Afiliação
  • Geng X; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Zhang D; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Suo S; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Chen J; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Cheng F; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Zhang K; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Zhang Q; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Li L; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Lu Y; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Hua J; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Zhuang Z; Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ann Transl Med ; 10(6): 323, 2022 Mar.
Article em En | MEDLINE | ID: mdl-35433990
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article