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Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting
Cellular microscopy images contain rich insights about biology. To extract this information, researchers use features, or measurements of the patterns of interest in the images. Here, we introduce a convolutional neural network (CNN) to automatically design features for fluorescence microscopy. We u...
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| 出版年: | PLoS Comput Biol |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6743779/ https://ncbi.nlm.nih.gov/pubmed/31479439 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1007348 |
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