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A Probabilistic Relaxation Labeling (PRL) Based Method for C. elegans Cell Tracking in Microscopic Image Sequences

机译:基于概率松弛标记(PRL)的秀丽隐杆线虫细胞在微观图像序列中的跟踪方法。

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摘要

Automatic cell tracking for 3D time-lapse images plays an important role in studying of live cell, which allows investigation of biological processes in vivo at the single cell resolution. In this paper, we propose a method for cell tracking during C. elegans embryogenesis based on probabilistic relaxation labeling (PRL). Instead of relying on the absolute cell position, we make use of the cell-to-cell relative position with two compatibility coefficients to achieve cell tracking. The tracking results obtained with this method are highly accurate with temporal resolution of one minute. In addition, our method can also been realized on multi-core CPUs, therefore providing an effective tool for analysis of large-scale data consisting of 3D time-lapse live cell images.
机译:3D延时图像的自动细胞跟踪在活细胞研究中起着重要作用,这使得可以在单细胞分辨率下研究体内的生物学过程。在本文中,我们提出了一种基于概率松弛标记(PRL)的秀丽隐杆线虫胚胎发生过程中的细胞追踪方法。而不是依赖于绝对的单元格位置,我们利用具有两个兼容性系数的单元格之间的相对位置来实现单元格跟踪。用这种方法获得的跟踪结果非常精确,时间分辨率为一分钟。此外,我们的方法也可以在多核CPU上实现,因此为分析由3D时移活细胞图像组成的大规模数据提供了有效的工具。

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