A comparison of deep learning U-Net architectures for posterior segment OCT retinal layer segmentation

Deep learning methods have enabled a fast, accurate and automated approach for retinal layer segmentation in posterior segment OCT images. Due to the success of semantic segmentation methods adopting the U-Net, a wide range of variants and improvements have been developed and applied to OCT segmenta...

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Detalles Bibliográficos
Autores principales: Kugelman, Jason, Allman, Joseph, Read, Scott A., Vincent, Stephen J., Tong, Janelle, Kalloniatis, Michael, Chen, Fred K., Collins, Michael J., Alonso-Caneiro, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437058/
https://www.ncbi.nlm.nih.gov/pubmed/36050364
http://dx.doi.org/10.1038/s41598-022-18646-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437058/
https://www.ncbi.nlm.nih.gov/pubmed/36050364
http://dx.doi.org/10.1038/s41598-022-18646-2

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