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Deep learning enables cross-modality super-resolution in fluorescence microscopy
We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on training a generative adversarial network (GAN) to...
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| Publicat a: | Nat Methods |
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| Autors principals: | , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7276094/ https://ncbi.nlm.nih.gov/pubmed/30559434 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41592-018-0239-0 |
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