Extracting quantitative measurements from time-lapse images is necessary in external feedback control applications, where segmentation results are used to inform control algorithms. While such image segmentation applications have been previously reported, there is in the literature a lack of open-source and documented code for the community. We describe ChipSeg, a computational tool to segment bacterial and mammalian cells cultured in microfluidic devices and imaged by time-lapse microscopy. The method is based on thresholding and uses the same core functions for both cell types. It allows to segment individual cells in high cell-density microfluidic devices, to quantify fluorescence protein expression over a time-lapse experiment and to track individual cells. ChipSeg enables robust segmentation in external feedback control experiments and can be easily customised for other experimental settings and research aims.

中文翻译：

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ChipSeg：一种自动工具，可对在微流控设备中培养的细菌和哺乳动物细胞进行分段

在外部反馈控制应用中，需要从延时图像中提取定量测量值，在这些应用中，分割结果用于告知控制算法。尽管先前已经报道过这种图像分割应用，但是在文献中缺少用于社区的开源和书面代码。我们描述了ChipSeg，一种用于分割在微流体设备中培养并通过延时显微镜成像的细菌和哺乳动物细胞的计算工具。该方法基于阈值，并且针对两种小区类型使用相同的核心功能。它允许在高细胞密度微流控设备中对单个细胞进行分段，以通过延时实验定量荧光蛋白表达并跟踪单个细胞。