Retinal Boundary Segmentation in Stargardt Disease Optical Coherence Tomography Images Using Automated Deep Learning

PURPOSE: To use a deep learning model to develop a fully automated method (fully semantic network and graph search [FS-GS]) of retinal segmentation for optical coherence tomography (OCT) images from patients with Stargardt disease. METHODS: Eighty-seven manually segmented (ground truth) OCT volume s...

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Detalles Bibliográficos
Autores principales: Kugelman, Jason, Alonso-Caneiro, David, Chen, Yi, Arunachalam, Sukanya, Huang, Di, Vallis, Natasha, Collins, Michael J., Chen, Fred K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581491/
https://www.ncbi.nlm.nih.gov/pubmed/33133774
http://dx.doi.org/10.1167/tvst.9.11.12

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581491/
https://www.ncbi.nlm.nih.gov/pubmed/33133774
http://dx.doi.org/10.1167/tvst.9.11.12

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