Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations.
Nat Biotechnol
; 41(1): 44-49, 2023 01.
Article
em En
| MEDLINE
| ID: mdl-36065022
ABSTRACT
We present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8% of cell lineages spanning 1 h, as compared to 31.8% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.
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Base de dados:
MEDLINE
Assunto principal:
Blastocisto
/
Embrião de Mamíferos
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article