Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning

IMPORTANCE: Quantitative volumetric measures of retinal disease in optical coherence tomography (OCT) scans are infeasible to perform owing to the time required for manual grading. Expert-level deep learning systems for automatic OCT segmentation have recently been developed. However, the potential...

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Detalles Bibliográficos
Autores principales: Wilson, Marc, Chopra, Reena, Wilson, Megan Z., Cooper, Charlotte, MacWilliams, Patricia, Liu, Yun, Wulczyn, Ellery, Florea, Daniela, Hughes, Cían O., Karthikesalingam, Alan, Khalid, Hagar, Vermeirsch, Sandra, Nicholson, Luke, Keane, Pearse A., Balaskas, Konstantinos, Kelly, Christopher J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444027/
https://www.ncbi.nlm.nih.gov/pubmed/34236406
http://dx.doi.org/10.1001/jamaophthalmol.2021.2273

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444027/
https://www.ncbi.nlm.nih.gov/pubmed/34236406
http://dx.doi.org/10.1001/jamaophthalmol.2021.2273

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