期刊
OPTICS EXPRESS
卷 16, 期 17, 页码 12943-12957出版社
OPTICAL SOC AMER
DOI: 10.1364/OE.16.012943
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资金
- Swedish Research Council
- Swedish Foundation for Strategic Research and Chalmers Biocenter
Quantification of protein abundance and subcellular localization dynamics from fluorescence microscopy images is of high contemporary interest in cell and molecular biology. For large-scale studies of cell populations and for time-lapse studies, such quantitative analysis can not be performed effectively without some kind of automated image analysis tool. Here, we present fast algorithms for automatic cell contour recognition in bright field images, optimized to the model organism budding yeast (Saccharomyces cerevisiae). The cell contours can be used to effectively quantify cell morphology parameters as well as protein abundance and subcellular localization from overlaid fluorescence data. (C) 2008 Optical Society of America.
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