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In-vitro cell quantification method based on depth dependent analysis of brain tissue microscopic images

机译:基于深度依赖分析的脑组织显微图像的体外细胞定量方法

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In this study we developed a new automatic quantification method to count the number of targeted fluorescently labeled molecules of in-vitro rat brain tissue images. NG2+ glial cells were monitored in order to detect their proliferation to their same kind of cells or to another astrocyte cells using different fluorescently labeled molecules. The method is based on morphological segmentation followed by depth-dependent detection operation applied to a stack of confocal microscopic images. The number of local maxima peak points was used to count the number of the labeled cells. The method shows good promise for the computer-aided assessment in neurological studies for accurate automatic counting systems.
机译:在这项研究中,我们开发了一种新的自动定量方法来计算体外大鼠脑组织图像中靶向荧光标记分子的数量。监测NG2 +神经胶质细胞,以便使用不同的荧光标记分子检测其向同类细胞或另一种星形胶质细胞的增殖。该方法基于形态学分割,然后将深度依赖的检测操作应用于共焦显微图像堆栈。局部最大峰点的数量用于计数标记细胞的数量。该方法为神经学研究中用于精确自动计数系统的计算机辅助评估显示出良好的前景。

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