Automated segmentation of the corneal endothelium in a large set of ‘real-world’ specular microscopy images using the U-Net architecture

Monitoring the density of corneal endothelial cells (CEC) is essential in the management of corneal diseases. Its manual calculation is time consuming and prone to errors. U-Net, a neural network for biomedical image segmentation, has shown promising results in the automated segmentation of images o...

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Detalles Bibliográficos
Autores principales: Daniel, Moritz C., Atzrodt, Lisa, Bucher, Felicitas, Wacker, Katrin, Böhringer, Stefan, Reinhard, Thomas, Böhringer, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426887/
https://www.ncbi.nlm.nih.gov/pubmed/30894636
http://dx.doi.org/10.1038/s41598-019-41034-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426887/
https://www.ncbi.nlm.nih.gov/pubmed/30894636
http://dx.doi.org/10.1038/s41598-019-41034-2

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