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Segmentation and quantitative analysis of the living tumor cells using Large Scale Digital Cell Analysis System

机译:使用大规模数字细胞分析系统对活体肿瘤细胞进行分割和定量分析

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The specific goal of our research is to develop automated methods for quantitative analysis of tumor cells from microscopic images. By segmenting living tumor cells, cell behavior under stress can be studied. Therefore, accurate acquisition and analysis of microscope images from living cell cultures are .of utmost importance. If cell behavior can be studied through their life span, cell motility and shape changes can be quantified and analyzed in relation with the severity of induced stress. Consequently, cell responses to the environment can be quantitatively analyzed. The Large Scale Digital Cell Analysis System developed at the University of Iowa provides a capability for real-time cell image acquisition. In the work presented here, feasibility of fully automated living tumor cell segmentation is demonstrated allowing future quantitative cell studies. An automated method for identification of the cell boundaries in microscopy images is presented.
机译:我们研究的特定目标是开发自动方法,以从显微图像定量分析肿瘤细胞。通过分割活的肿瘤细胞,可以研究在压力下的细胞行为。因此,从活细胞培养物中准确采集和分析显微镜图像至关重要。如果可以在整个生命周期内研究细胞行为,那么就可以根据诱导的压力的严重程度对细胞运动性和形状变化进行量化和分析。因此,可以定量分析细胞对环境的反应。爱荷华大学开发的大规模数字细胞分析系统提供了实时细胞图像采集的功能。在本文介绍的工作中,展示了全自动活体肿瘤细胞分割的可行性,从而可以进行未来的定量细胞研究。提出了一种在显微镜图像中鉴定细胞边界的自动化方法。

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