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An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.
Burke, Jamie; Engelmann, Justin; Hamid, Charlene; Reid-Schachter, Megan; Pearson, Tom; Pugh, Dan; Dhaun, Neeraj; Storkey, Amos; King, Stuart; MacGillivray, Tom J; Bernabeu, Miguel O; MacCormick, Ian J C.
Afiliação
  • Burke J; School of Mathematics, University of Edinburgh, Edinburgh, UK.
  • Engelmann J; School of Informatics, University of Edinburgh, Edinburgh, UK.
  • Hamid C; Centre for Medical Informatics, University of Edinburgh, Edinburgh, UK.
  • Reid-Schachter M; Clinical Research Facility and Imaging, University of Edinburgh, Edinburgh, UK.
  • Pearson T; Clinical Research Facility and Imaging, University of Edinburgh, Edinburgh, UK.
  • Pugh D; University Hospital Wales, NHS Wales, Cardiff, Wales, UK.
  • Dhaun N; British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • Storkey A; British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • King S; Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, UK.
  • MacGillivray TJ; School of Mathematics, University of Edinburgh, Edinburgh, UK.
  • Bernabeu MO; Clinical Research Facility and Imaging, University of Edinburgh, Edinburgh, UK.
  • MacCormick IJC; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Transl Vis Sci Technol ; 12(11): 27, 2023 11 01.
Article em En | MEDLINE | ID: mdl-37988073
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oftalmologistas / Aprendizado Profundo Limite: Humans Idioma: En Revista: Transl Vis Sci Technol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oftalmologistas / Aprendizado Profundo Limite: Humans Idioma: En Revista: Transl Vis Sci Technol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido