Applications of Deep Learning: Automated Assessment of Vascular Tortuosity in Mouse Models of Oxygen-Induced Retinopathy

OBJECTIVE: To develop a generative adversarial network (GAN) to segment major blood vessels from retinal flat-mount images from oxygen-induced retinopathy (OIR) and demonstrate the utility of these GAN-generated vessel segmentations in quantifying vascular tortuosity. DESIGN: Development and validat...

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Detalles Bibliográficos
Autores principales: Chen, Jimmy S., Marra, Kyle V., Robles-Holmes, Hailey K., Ly, Kristine B., Miller, Joseph, Wei, Guoqin, Aguilar, Edith, Bucher, Felicitas, Ideguchi, Yoichi, Coyner, Aaron S., Ferrara, Napoleone, Campbell, J. Peter, Friedlander, Martin, Nudleman, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585474/
https://www.ncbi.nlm.nih.gov/pubmed/37869029
http://dx.doi.org/10.1016/j.xops.2023.100338

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585474/
https://www.ncbi.nlm.nih.gov/pubmed/37869029
http://dx.doi.org/10.1016/j.xops.2023.100338

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