Minimal paths and probabilistic models for origin-destination traffic estimation in live cell imaging

机译：Live Cell成像中原始目标流量估计的最小路径和概率模型

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Green Fluorescent Protein (GFP)-tagging and time-lapse fluorescence microscopy enable to observe molecular dynamics and interactions in live cells. Original image analysis methods are then required to process challenging 2D or 3D image sequences. To addre

机译：绿色荧光蛋白（GFP） - 可延时荧光显微镜可使观察活细胞的分子动力学和相互作用。然后需要原始图像分析方法来处理具有挑战性的2D或3D图像序列。到addre.

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《IEEE International Symposium on Biomedical Imaging》|2008年||共4页
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Pecot T.; Kervrann C.; Bouthemy P.;
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中图分类 TP391.4-53;
关键词
cellular transport; fluorescence; image sequences; medical image processing; molecular biophysics; proteins; 2D image sequence; 3D image sequence; GFP-tagging; Rab protein; green fluorescent protein; image partition; live cell imaging; minimal paths; molecular dynamic;

机译：细胞传输;荧光;图像序列;医学图像处理;分子生物物理学;蛋白质;2D图像序列;3D图像序列;GFP标记;RAB蛋白;绿色荧光蛋白;图像分区;最小路径;分子动感;

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4. Minimal paths and probabilistic models for origin-destination traffic estimation in live cell imaging [C] . Pecot T., Kervrann C., Bouthemy P. IEEE International Symposium on Biomedical Imaging . 2008

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7. Minimal paths and probabilistic models for origin-destination traffic estimation in live cell imaging [O] . T. Pécot, C. Kervrann, P. Bouthemy, 2010

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Minimal paths and probabilistic models for origin-destination traffic estimation in live cell imaging

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