Cargando…
Segmentation and Evaluation of Corneal Nerves and Dendritic Cells From In Vivo Confocal Microscopy Images Using Deep Learning
PURPOSE: Segmentation and evaluation of in vivo confocal microscopy (IVCM) images requires manual intervention, which is time consuming, laborious, and non-reproducible. The aim of this research was to develop and validate deep learning–based methods that could automatically segment and evaluate cor...
Autores principales: | Setu, Md Asif Khan, Schmidt, Stefan, Musial, Gwen, Stern, Michael E., Steven, Philipp |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251793/ https://www.ncbi.nlm.nih.gov/pubmed/35762938 http://dx.doi.org/10.1167/tvst.11.6.24 |
Ejemplares similares
-
A Deep Learning Model for Automated Sub-Basal Corneal Nerve Segmentation and Evaluation Using In Vivo Confocal Microscopy
por: Wei, Shanshan, et al.
Publicado: (2020) -
Corneal confocal microscopy detects corneal nerve damage and increased dendritic cells in Fabry disease
por: Bitirgen, Gulfidan, et al.
Publicado: (2018) -
Generative Adversarial Network Based Automatic Segmentation of Corneal Subbasal Nerves on In Vivo Confocal Microscopy Images
por: Yıldız, Erdost, et al.
Publicado: (2021) -
Evaluation of corneal nerves and dendritic cells by in vivo confocal microscopy after Descemet’s membrane keratoplasty for bullous keratopathy
por: Shimizu, Toshiki, et al.
Publicado: (2022) -
Deep learning-based automatic meibomian gland segmentation and morphology assessment in infrared meibography
por: Setu, Md Asif Khan, et al.
Publicado: (2021)