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1 Publications

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    01/01/23 | Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations.
    Malin-Mayor C, Hirsch P, Guignard L, McDole K, Wan Y, Lemon WC, Kainmueller D, Keller PJ, Preibisch S, Funke J
    Nature Biotechnology. 2023 Jan 01;41(1):44-49. doi: 10.1038/s41587-022-01427-7

    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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