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Segmentation, tracking and lineage analysis of yeast cells in bright field microscopy images

机译:明亮视野显微镜图像中酵母细胞的分割,跟踪和谱系分析

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摘要

Summary. — Time lapse microscopy images are an important support in quantitative biology. Gene circuit dynamics can be precisely estimated at a single-cell level but automatic cell segmentation and tracking are required due to the large number of cells under study and the large amount of images to be analyzed. Here we present a solution for segmentation, tracking and lineage analysis of yeast cells in bright field, phase contrast microscopy images. The solution is designed to be applied with little effort by biologists thanks to the robust global linking segmentation approach and a pattern recognition-based false-positive detection system. Performance evaluation methods are also introduced and used for a reliable evaluation of our method. Moreover, we show here that our method achieves competitive performances with existing methods without time-consuming optimal parameters search. PACS 87.18.Vf - Systems biology. PACS 87.17. Aa - Modeling, computer simulation of cell processes.
机译:概要。 —延时显微镜图像是定量生物学的重要支持。可以在单细胞水平上精确估计基因电路动力学,但由于研究中的细胞数量众多且需要分析的图像很多,因此需要自动的细胞分段和跟踪。在这里,我们提出了一种在明场,相衬显微镜图像中对酵母细胞进行分割,跟踪和谱系分析的解决方案。由于强大的全局链接分割方法和基于模式识别的假阳性检测系统,该解决方案的设计目的是使生物学家毫不费力地应用该解决方案。还介绍了性能评估方法,并将其用于对我们方法的可靠评估。此外,我们在这里表明,我们的方法在不耗时的最佳参数搜索的情况下,与现有方法相比具有竞争优势。 PACS 87.18.Vf-系统生物学。 PACS 87.17。 Aa-建模,细胞过程的计算机模拟。

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