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• W3208613794 abstract "Experimental studies of cell growth, inheritance, and their associated processes by microscopy require accurate single-cell observations of sufficient duration to reconstruct the genealogy. However, cell tracking—assigning identical cells on consecutive images to a track—is often challenging due to imperfect segmentation, moving cells, or focus drift, resulting in laborious manual verification. Here, we propose fingerprints to identify problematic assignments rapidly. A fingerprint distance measures the similarity between cells in two consecutive images by comparing the structural information contained in the low frequencies of a Fourier transform. We show that it is broadly applicable across cell types and image modalities, provided the image has sufficient structural information. Our tracker ( Trac X ) uses the concept to reject unlikely assignments, thereby substantially increasing tracking performance on published and newly generated long-term data sets from various species. For S. cerevisiae , we propose a comprehensive model for cell size control at the single-cell and population level centered on the Whi5 regulator. It demonstrates how highly precise tracking can help uncover previously undescribed single-cell biology." @default.
• W3208613794 created "2021-11-08" @default.
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• W3208613794 date "2021-10-28" @default.
• W3208613794 modified "2023-10-04" @default.
• W3208613794 title "Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction" @default.
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• W3208613794 doi "https://doi.org/10.1101/2021.10.26.465883" @default.
• W3208613794 hasPublicationYear "2021" @default.
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