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Parallel deep neural networks for endoscopic OCT image segmentation
We report parallel-trained deep neural networks for automated endoscopic OCT image segmentation feasible even with a limited training data set. These U-Net-based deep neural networks were trained using a modified dice loss function and manual segmentations of ultrahigh-resolution cross-sectional ima...
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| Publicado en: | Biomed Opt Express |
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| Autores principales: | , , , , , , , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Optical Society of America
2019
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6420296/ https://ncbi.nlm.nih.gov/pubmed/30891334 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1364/BOE.10.001126 |
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