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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743779/ https://www.ncbi.nlm.nih.gov/pubmed/31479439 http://dx.doi.org/10.1371/journal.pcbi.1007348 |