Virtual Staining of Defocused Autofluorescence Images of Unlabeled Tissue Using Deep Neural Networks
Deep learning-based virtual staining was developed to introduce image contrast to label-free tissue sections, digitally matching the histological staining, which is time-consuming, labor-intensive, and destructive to tissue. Standard virtual staining requires high autofocusing precision during the w...
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| Glavni autori: | , , , , , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
American Association for the Advancement of Science (AAAS)
2022-01-01
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| Serija: | Intelligent Computing |
| Online pristup: | https://spj.science.org/doi/10.34133/2022/9818965 |
| Oznake: |
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