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3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis
During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To acquire quantitative criteria of embryogenesis from...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575569/ https://www.ncbi.nlm.nih.gov/pubmed/33082352 http://dx.doi.org/10.1038/s41540-020-00152-8 |