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...

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Detalles Bibliográficos
Autores principales: Tokuoka, Yuta, Yamada, Takahiro G., Mashiko, Daisuke, Ikeda, Zenki, Hiroi, Noriko F., Kobayashi, Tetsuya J., Yamagata, Kazuo, Funahashi, Akira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
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

Internet

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

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