Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning.

Schwarzenbacher, Luca; Seeböck, Philipp; Schartmüller, Daniel; Leydolt, Christina; Menapace, Rupert; Schmidt-Erfurth, Ursula

Schwarzenbacher, Luca; Seeböck, Philipp; Schartmüller, Daniel; Leydolt, Christina; Menapace, Rupert; Schmidt-Erfurth, Ursula.

Afiliação

Schwarzenbacher L; Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Seeböck P; Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Schartmüller D; Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Leydolt C; Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Menapace R; Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Schmidt-Erfurth U; Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

Acta Ophthalmol ; 100(8): e1611-e1616, 2022 Dec.

Article em En | MEDLINE | ID: mdl-35343651

Assuntos

Aprendizado Profundo; Lentes Intraoculares; Humanos; Implante de Lente Intraocular; Inteligência Artificial; Estudos Transversais; Tomografia de Coerência Óptica/métodos

Palavras-chave

Berger space; IOL; OCT; PPLC; artificial intelligence; cataract surgery; deep learning; femtosecond laser; retrolental space

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Lentes Intraoculares Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo

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PubMed Links

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Lentes Intraoculares Idioma: En Ano de publicação: 2022 Tipo de documento: Article