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Traxtile: Interactive editing of cell tracks in time-lapse images

机译:Traxtile:对延时图像中的细胞轨迹进行交互式编辑

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摘要

Time-lapse imaging can be used to quantify how cells move, divide, and die over time and under defined culture conditions. Open source software packages such as CellProfiler, Icy, and Fiji provide robust and convenient interfaces for performing such analyses. However, object tracking algorithms are imperfect, and validation of significant events is often required. This is challenging, as CellProfiler produces only tabular data for object tracking, and the graphical tools in Icy and Fiji are not optimal for manual review of these events. Here we describe Traxtile, a program that allows interactive graphical review and revision of object tracking assignments. Traxtile imports initial assignments and automatically identifies events needing review (i.e., apparent creation of new objects, splits, merges, and losses). For each such event, the object track is displayed on a montage of images centered on the event and spanning the preceding and subsequent frames. Links between cells in successive frames can be reviewed and edited, yielding validated tracks for the image series. Reports summarize events from the validated tracks. Traxtile is implemented in Python version 2.7 using standard distribution libraries (available at ) and is freely available at .
机译:延时成像可用于量化细胞在定义的培养条件下如何随时间运动,分裂和死亡。诸如CellProfiler,Icy和Fiji之类的开源软件包为执行此类分析提供了强大而便捷的界面。但是,对象跟踪算法并不完善,通常需要对重大事件进行验证。这具有挑战性,因为CellProfiler仅生成用于对象跟踪的表格数据,而Icy和Fiji中的图形工具并不是手动查看这些事件的最佳选择。在这里,我们介绍Traxtile,这是一个允许对对象跟踪分配进行交互式图形检查和修订的程序。 Traxtile会导入初始任务并自动识别需要检查的事件(即新对象的明显创建,拆分,合并和丢失)。对于每个此类事件,对象轨迹将显示在以事件为中心并跨越前后帧的图像蒙太奇上。可以检查和编辑连续帧中的单元格之间的链接,从而生成图像系列的经过验证的轨道。报告总结了来自已验证轨道的事件。 Traxtile是在Python 2.7版中使用标准分发库(在处提供)实现的,可在处免费获得。

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