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Retinal image synthesis from multiple-landmarks input with generative adversarial networks
BACKGROUND: Medical datasets, especially medical images, are often imbalanced due to the different incidences of various diseases. To address this problem, many methods have been proposed to synthesize medical images using generative adversarial networks (GANs) to enlarge training datasets for facil...
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| Veröffentlicht in: | Biomed Eng Online |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
BioMed Central
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6528202/ https://ncbi.nlm.nih.gov/pubmed/31113438 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12938-019-0682-x |
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