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- W4301595725 abstract "Abstract Comprehensive analysis of tissue composition has so far been limited to ex vivo approaches. Here, we introduce NuClear ( Nu cleus-instructed tissue c omposition using deep lear ning), an approach combining in vivo two-photon imaging of histone 2B-eGFP-labeled cell nuclei with subsequent deep learning-based identification of cell types from structural features of the respective cell nuclei. This allowed us to classify all cells per imaging volume (0.25 mm 3 containing ~25000 cells) and identify their position in 3D space in a non-invasive manner using only a single label. NuClear opens a window to study changes in relative abundance and location of all major brain cell types in individual mice over extended time periods, enabling comprehensive studies of changes in cellular composition in physiological and pathophysiological conditions." @default.
- W4301595725 created "2022-10-05" @default.
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- W4301595725 date "2022-10-05" @default.
- W4301595725 modified "2023-10-14" @default.
- W4301595725 title "Comprehensive monitoring of tissue composition using in vivo imaging of cell nuclei and deep learning" @default.
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- W4301595725 doi "https://doi.org/10.1101/2022.10.03.510670" @default.
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