A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input.

Islam, Mohammad Shafkat; Wang, Jui-Kai; Johnson, Samuel S; Thurtell, Matthew J; Kardon, Randy H; Garvin, Mona K

Islam, Mohammad Shafkat; Wang, Jui-Kai; Johnson, Samuel S; Thurtell, Matthew J; Kardon, Randy H; Garvin, Mona K.

Afiliação

Islam MS; Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA.
Wang JK; Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA.
Johnson SS; Iowa City VA Health Care System and Iowa City VA Center for the Prevention and Treatment of Visual Loss, Iowa City, IA, USA.
Thurtell MJ; Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA.
Kardon RH; Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA.
Garvin MK; Iowa City VA Health Care System and Iowa City VA Center for the Prevention and Treatment of Visual Loss, Iowa City, IA, USA.

Transl Vis Sci Technol ; 9(2): 17, 2020 03.

Article em En | MEDLINE | ID: mdl-32821471

Assuntos

Aprendizado Profundo; Disco Óptico; Papiledema; Vasos Retinianos; Humanos; Disco Óptico/diagnóstico por imagem; Vasos Retinianos/diagnóstico por imagem; Tomografia de Coerência Óptica

Palavras-chave

U-Net; deep learning; multiple en-face images; optic disc swelling; optical coherence tomography; papilledema; retinal blood vessels; vessel segmentation

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Disco Óptico / Vasos Retinianos / Papiledema / Aprendizado Profundo Tipo de estudo: Clinical_trials Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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