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Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images
PURPOSE: To automatically and accurately segment geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images by constructing a voting system with deep neural networks without the use of retinal layer segmentation. METHODS: An automatic GA segmentation method for SD-OCT im...
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| 出版年: | Transl Vis Sci Technol |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
The Association for Research in Vision and Ophthalmology
2018
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5749649/ https://ncbi.nlm.nih.gov/pubmed/29302382 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/tvst.7.1.1 |
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