Your browser doesn't support javascript.
loading
A deep learning-based pipeline for analyzing the influences of interfacial mechanochemical microenvironments on spheroid invasion using differential interference contrast microscopic images.
Ngo, Thi Kim Ngan; Yang, Sze Jue; Mao, Bin-Hsu; Nguyen, Thi Kim Mai; Ng, Qi Ding; Kuo, Yao-Lung; Tsai, Jui-Hung; Saw, Shier Nee; Tu, Ting-Yuan.
Afiliação
  • Ngo TKN; Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan, 70101, Taiwan.
  • Yang SJ; Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia.
  • Mao BH; Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan, 70101, Taiwan.
  • Nguyen TKM; Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan, 70101, Taiwan.
  • Ng QD; Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia.
  • Kuo YL; Department of Surgery, College of Medicine, National Cheng Kung University, Tainan, 70101, Taiwan.
  • Tsai JH; Department of Surgery, National Cheng Kung University Hospital, Tainan, 70101, Taiwan.
  • Saw SN; Department of Internal Medicine, National Cheng Kung University Hospital, Tainan, 70101, Taiwan.
  • Tu TY; Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Mater Today Bio ; 23: 100820, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37810748
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Mater Today Bio Ano de publicação: 2023 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 Idioma: En Revista: Mater Today Bio Ano de publicação: 2023 Tipo de documento: Article