Deep learning based retinal hard exudates quantification of optical coherence tomography
Abstract Purpose To develop a deep learning (DL) model for segmenting retinal hard exudates (HE) from optical coherence tomography (OCT) scans. Methods A modified U-Net architecture was trained on manually segmented OCT B-scans of retinal HE. The training set included 1,811 OCT scans from 15 patient...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
BMC
2025-10-01
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| Schriftenreihe: | International Journal of Retina and Vitreous |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1186/s40942-025-00715-z |
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