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Population Estimation of Human Embryonic Stem Cell Cultures

机译:人类胚胎干细胞培养的种群估计

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Traditionally, the population of human embryonic stem cell (hESC) culture is estimated through haemacytometer counts, which include harvesting the cells and manually analyzing a fraction of an entire population. Obviously, through this highly invasive method, it is not possible to preserve any spatial information on the cell population. The goal of this study is to identify a fast and consistent method for in situ automated hESC population estimation to quantitatively estimate the cell growth. Therefore, cell cultures were fixed, stained, and their nuclei imaged through high-resolution microscopy, and the images were processed with different image analysis techniques. The proposed method first identifies signal and background by computing an image specific threshold for image segmentation. By applying a morphological operator (watershed), we split most physically overlapping nuclei, leading to a pixel area distribution of isolated signal areas on the image. On the basis of this distribution, we derive a nucleus area model, describing the distribution of the area of cell debris, single nuclei, and small groups of connected nuclei. Through the model, we can give a quantitative estimation of the population. The focus of this study is on low-density human embryonic stem cell populations; hence cultures were measured at days 2-3 after seeding. Compared with manual cell counts, the automatic method achieved higher accuracy with <6% error.
机译:传统上,人类胚胎干细胞(hESC)培养的数量是通过血球计数器来估算的,其中包括收获细胞并手动分析整个种群的一部分。显然,通过这种高度侵入性的方法,不可能在细胞群上保留任何空间信息。这项研究的目的是为原位自动hESC群体估计确定一种快速一致的方法,以定量估计细胞的生长。因此,将细胞培养物固定,染色,并通过高分辨率显微镜对细胞核进行成像,并使用不同的图像分析技术对图像进行处理。所提出的方法首先通过计算用于图像分割的图像特定阈值来识别信号和背景。通过应用形态学算子(分水岭),我们分裂了大多数物理上重叠的核,从而导致图像上孤立信号区域的像素区域分布。在此分布的基础上,我们导出了一个原子核面积模型,描述了细胞碎片,单个原子核以及连接的原子核的小群区域的分布。通过该模型,我们可以对人口进行定量估计。这项研究的重点是低密度的人类胚胎干细胞群体。因此,在接种后第2-3天测量培养物。与手动细胞计数相比,自动方法获得了更高的准确度,误差小于6%。

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