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Deep Learning-Based Automated Classification of Multi-Categorical Abnormalities From Optical Coherence Tomography Images
PURPOSE: To develop a new intelligent system based on deep learning for automatically optical coherence tomography (OCT) images categorization. METHODS: A total of 60,407 OCT images were labeled by 17 licensed retinal experts and 25,134 images were included. One hundred one-layer convolutional neura...
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| Gepubliceerd in: | Transl Vis Sci Technol |
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| Hoofdauteurs: | , , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
The Association for Research in Vision and Ophthalmology
2018
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6314222/ https://ncbi.nlm.nih.gov/pubmed/30619661 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/tvst.7.6.41 |
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