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Performance evaluation of a deep learning-based cascaded HRNet model for automatic measurement of X-ray imaging parameters of lumbar sagittal curvature.
Wu, Yuhua; Chen, Xiaofei; Dong, Fuwen; He, Linyang; Cheng, Guohua; Zheng, Yuwen; Ma, Chunyu; Yao, Hongyan; Zhou, Sheng.
Afiliação
  • Wu Y; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China.
  • Chen X; Department of Radiology, Gansu Provincial Hospital of Traditional Chinese Medicine (The first affiliated hospital of Gansu University of Traditional Chinese Medicine), Lanzhou, 730050, Gansu, China.
  • Dong F; Department of Radiology, Gansu Provincial Hospital of Traditional Chinese Medicine (The first affiliated hospital of Gansu University of Traditional Chinese Medicine), Lanzhou, 730050, Gansu, China.
  • He L; Hangzhou Jianpei Technology Company Ltd, Hangzhou, 311200, Zhejiang, China.
  • Cheng G; Hangzhou Jianpei Technology Company Ltd, Hangzhou, 311200, Zhejiang, China.
  • Zheng Y; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China.
  • Ma C; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China.
  • Yao H; Department of Radiology, Gansu Provincial Hospital, No. 204, Donggang West Road, Lanzhou, 730000, Gansu, China.
  • Zhou S; Department of Radiology, Gansu Provincial Hospital, No. 204, Donggang West Road, Lanzhou, 730000, Gansu, China. lzzs@sina.com.
Eur Spine J ; 2023 Oct 03.
Article em En | MEDLINE | ID: mdl-37787781
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: Eur Spine J Assunto da revista: ORTOPEDIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: Eur Spine J Assunto da revista: ORTOPEDIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China