VISGAB: Virtual staining-driven GAN benchmarking for optimizing skin tissue histology
Abstract Hematoxylin and eosin (H&E) staining is time-consuming, costly, hazardous, and prone to technician-dependent quality variations. This calls for fast, low-cost, and standardized computational alternatives. Lately, generative adversarial networks (GANs) have shown promising results by generat...
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| Hlavní autoři: | , , , , , , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Nature Portfolio
2025-11-01
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| Edice: | Scientific Reports |
| Témata: | |
| On-line přístup: | https://doi.org/10.1038/s41598-025-26493-0 |
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