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A deep learning model for detection and tracking in high-throughput images of organoid.
Bian, Xuesheng; Li, Gang; Wang, Cheng; Liu, Weiquan; Lin, Xiuhong; Chen, Zexin; Cheung, Mancheung; Luo, Xiongbiao.
Afiliação
  • Bian X; Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, 361005, China. Electronic address: xsbian@stu.xmu.edu.cn.
  • Li G; Nanfang Hospital, Southern Medical University, Guangzhou, 510000, China. Electronic address: lg@smu.edu.cn.
  • Wang C; Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, 361005, China. Electronic address: cwang@xmu.edu.cn.
  • Liu W; Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, 361005, China. Electronic address: wqliu@xmu.edu.cn.
  • Lin X; Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, 361005, China. Electronic address: xhlinxm@qq.com.
  • Chen Z; Accurate International Biotechnology (GZ) Co., Ltd, Guangzhou, 510000, China. Electronic address: czxchase@126.com.
  • Cheung M; Accurate International Biotechnology (GZ) Co., Ltd, Guangzhou, 510000, China. Electronic address: zhangminxiang@accibio.com.
  • Luo X; Fujian Key Laboratory of Sensing and Computing for Smart City, School of Informatics, Xiamen University, Xiamen, 361005, China. Electronic address: xbluo@xmu.edu.cn.
Comput Biol Med ; 134: 104490, 2021 07.
Article em En | MEDLINE | ID: mdl-34102401
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Organoides / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Comput Biol Med Ano de publicação: 2021 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Organoides / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Comput Biol Med Ano de publicação: 2021 Tipo de documento: Article