We develop automated approaches to computer vision to efficiently convert the raw image data of each recorded embryo into biologically meaningful, digital representations. This step provides "digital embryos", i.e. detailed information on cell lineages and cell-cell interactions throughout the developing embryo (Keller et al. 2008, Science; Amat et al. 2014, Nature Methods). Morphological information and spatiotemporal dynamics of gene expression can be resolved at the same time and correlated at the system level. This approach allows us to reverse-engineer the developmental building plans of tissues and organs in the whole-embryo context and, thus, to analyze development of the entire organism systematically.
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Automated Approaches to Computer Vision
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