Open source software for automatic detection of cone photoreceptors in adaptive optics ophthalmoscopy using convolutional neural networks

Imaging with an adaptive optics scanning light ophthalmoscope (AOSLO) enables direct visualization of the cone photoreceptor mosaic in the living human retina. Quantitative analysis of AOSLO images typically requires manual grading, which is time consuming, and subjective; thus, automated algorithms...

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Detalles Bibliográficos
Autores principales: Cunefare, David, Fang, Leyuan, Cooper, Robert F., Dubra, Alfredo, Carroll, Joseph, Farsiu, Sina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529414/
https://www.ncbi.nlm.nih.gov/pubmed/28747737
http://dx.doi.org/10.1038/s41598-017-07103-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529414/
https://www.ncbi.nlm.nih.gov/pubmed/28747737
http://dx.doi.org/10.1038/s41598-017-07103-0

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