Automatic analysis framework based on 3D-CT multi-scale features for accurate prediction of Ki67 expression levels in substantial renal cell carcinoma.

Yang, Huancheng; Lin, Jiashan; Liu, Hanlin; Yao, Jiehua; Lin, Qianyu; Wang, Jiaxin; Jiang, Feiye; Wei, Liying; Lin, Chongyang; Wu, Kai; Wu, Song

Yang, Huancheng; Lin, Jiashan; Liu, Hanlin; Yao, Jiehua; Lin, Qianyu; Wang, Jiaxin; Jiang, Feiye; Wei, Liying; Lin, Chongyang; Wu, Kai; Wu, Song.

Afiliação

Yang H; Luohu Clinical Institute, Shantou University Medical College, Shantou, 515000, China.
Lin J; Shenzhen Following Precision Medical Research Institute, Luohu Hospital Group, Shenzhen, 51800, China.
Liu H; Shantou University Medical College, Shantou University, Shantou, 515000, China.
Yao J; Luohu Clinical Institute, Shantou University Medical College, Shantou, 515000, China.
Lin Q; Shantou University Medical College, Shantou University, Shantou, 515000, China.
Wang J; Department of Urology, Peking University Shenzhen Hospital, Shenzhen, 518036, China.
Jiang F; Department of Radiology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen, 518000, China.
Wei L; Shantou University Medical College, Shantou University, Shantou, 515000, China.
Lin C; Shantou University Medical College, Shantou University, Shantou, 515000, China.
Wu K; Shantou University Medical College, Shantou University, Shantou, 515000, China.
Wu S; Shantou University Medical College, Shantou University, Shantou, 515000, China.

Insights Imaging ; 14(1): 130, 2023 Jul 19.

Article em En | MEDLINE | ID: mdl-37466878

Palavras-chave

Ki67; Multi-scale features; Renal cell carcinoma

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Insights Imaging Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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