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Estimating Cell Count and Distribution in Labeled Histological Samples Using Incremental Cell Search

机译:使用增量细胞搜索估算标记的组织学样品中的细胞计数和分布

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Cell proliferation is critical to the outgrowth of biological structures including the face and limbs. This cellular process has traditionally been studied via sequential histological sampling of these tissues. The length and tedium of traditional sampling is a major impediment to analyzing the large datasets required to accurately model cellular processes. Computerized cell localization and quantification is critical for high-throughput morphometric analysis of developing embryonic tissues. We have developed the Incremental Cell Search (ICS), a novel software tool that expedites the analysis of relationships between morphological outgrowth and cell proliferation in embryonic tissues. Based on an estimated average cell size and stain color, ICS rapidly indicates the approximate location and amount of cells in histological images of labeled embryonic tissue and provides estimates of cell counts in regions with saturated fluorescence and blurred cell boundaries. This capacity opens the door to high-throughput 3D and 4D quantitative analyses of developmental patterns.
机译:细胞增殖对于包括面部和四肢在内的生物结构的生长至关重要。传统上已经通过对这些组织进行连续组织学取样研究了该细胞过程。传统采样的长度和繁琐是分析精确建模细胞过程所需的大型数据集的主要障碍。计算机化的细胞定位和定量对于发育中的胚胎组织的高通量形态分析至关重要。我们已经开发了增量细胞搜索(ICS),这是一种新颖的软件工具,可以加快对形态学增长与胚胎组织中细胞增殖之间关系的分析。基于估计的平均细胞大小和染色颜色,ICS可以快速显示标记的胚胎组织的组织学图像中细胞的大概位置和数量,并提供具有饱和荧光和模糊细胞边界的区域中的细胞计数估计值。这种能力为开发模式的高通量3D和4D定量分析打开了大门。

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