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Visual Field Inference From Optical Coherence Tomography Using Deep Learning Algorithms: A Comparison Between Devices
PURPOSE: To develop a deep learning model to estimate the visual field (VF) from spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT) and to compare the performance between them. METHODS: Two deep learning models based on Inception-ResNet-v2 were trained to estimate 24...
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| I publikationen: | Transl Vis Sci Technol |
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| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
The Association for Research in Vision and Ophthalmology
2021
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8185404/ https://ncbi.nlm.nih.gov/pubmed/34086043 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/tvst.10.7.4 |
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