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Automated Segmentation of Retinal Fluid Volumes From Structural and Angiographic Optical Coherence Tomography Using Deep Learning
PURPOSE: We proposed a deep convolutional neural network (CNN), named Retinal Fluid Segmentation Network (ReF-Net), to segment retinal fluid in diabetic macular edema (DME) in optical coherence tomography (OCT) volumes. METHODS: The 3- × 3-mm OCT scans were acquired on one eye by a 70-kHz OCT commer...
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| Pubblicato in: | Transl Vis Sci Technol |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
The Association for Research in Vision and Ophthalmology
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7552937/ https://ncbi.nlm.nih.gov/pubmed/33110708 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/tvst.9.2.54 |
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