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Deep Learning Applied to Automated Segmentation of Geographic Atrophy in Fundus Autofluorescence Images
PURPOSE: This study describes the development of a deep learning algorithm based on the U-Net architecture for automated segmentation of geographic atrophy (GA) lesions in fundus autofluorescence (FAF) images. METHODS: Image preprocessing and normalization by modified adaptive histogram equalization...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Association for Research in Vision and Ophthalmology
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8267211/ https://www.ncbi.nlm.nih.gov/pubmed/34228106 http://dx.doi.org/10.1167/tvst.10.8.2 |