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Deep Learning Approaches Predict Glaucomatous Visual Field Damage from Optical Coherence Tomography Optic Nerve Head Enface Images and Retinal Nerve Fiber Layer Thickness Maps
PURPOSE: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain optical coherence tomography (SDOCT) optic nerve head images. DESIGN: Evaluation of a diagnostic...
Gorde:
| Argitaratua izan da: | Ophthalmology |
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| Egile Nagusiak: | , , , , , , , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2019
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8063221/ https://ncbi.nlm.nih.gov/pubmed/31718841 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ophtha.2019.09.036 |
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