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• W1987712963 abstract "Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology." @default.
• W1987712963 created "2016-06-24" @default.
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• W1987712963 date "2013-07-24" @default.
• W1987712963 modified "2023-09-25" @default.
• W1987712963 title "Fast and accurate automated cell boundary determination for fluorescence microscopy" @default.
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• W1987712963 doi "https://doi.org/10.1038/srep02266" @default.
• W1987712963 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3721074" @default.
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• W1987712963 hasPublicationYear "2013" @default.
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