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A comparison of deep learning U-Net architectures for posterior segment OCT retinal layer segmentation.
Kugelman, Jason; Allman, Joseph; Read, Scott A; Vincent, Stephen J; Tong, Janelle; Kalloniatis, Michael; Chen, Fred K; Collins, Michael J; Alonso-Caneiro, David.
Afiliação
  • Kugelman J; Contact Lens and Visual Optics Laboratory, Centre for Vision and Eye Research, School of Optometry and Vision Science, Queensland University of Technology (QUT), Kelvin Grove, Australia. j.kugelman@qut.edu.au.
  • Allman J; Contact Lens and Visual Optics Laboratory, Centre for Vision and Eye Research, School of Optometry and Vision Science, Queensland University of Technology (QUT), Kelvin Grove, Australia.
  • Read SA; Contact Lens and Visual Optics Laboratory, Centre for Vision and Eye Research, School of Optometry and Vision Science, Queensland University of Technology (QUT), Kelvin Grove, Australia.
  • Vincent SJ; Contact Lens and Visual Optics Laboratory, Centre for Vision and Eye Research, School of Optometry and Vision Science, Queensland University of Technology (QUT), Kelvin Grove, Australia.
  • Tong J; Centre for Eye Health, University of New South Wales (UNSW), Sydney, NSW, Australia.
  • Kalloniatis M; School of Optometry and Vision Science, UNSW, Sydney, NSW, Australia.
  • Chen FK; Centre for Eye Health, University of New South Wales (UNSW), Sydney, NSW, Australia.
  • Collins MJ; School of Optometry and Vision Science, UNSW, Sydney, NSW, Australia.
  • Alonso-Caneiro D; Centre for Ophthalmology and Visual Science (Incorporating Lions Eye Institute), The University of Western Australia, Perth, WA, Australia.
Sci Rep ; 12(1): 14888, 2022 09 01.
Article em En | MEDLINE | ID: mdl-36050364
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article