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Practical Considerations in Particle and Object Tracking and Analysis

机译：粒子和物体跟踪和分析中的实际考虑

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The rapid advancement of live-cell imaging technologies has enabled biologists to generate high-dimensional data to follow biological movement at the microscopic level. Yet, the "perceived" ease of use of modern microscopes has led to challenges whereby sub-optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill-advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image-processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with adiscussion of how movement behavior can be mathematically modeled and described.
机译：Live-Cell成像技术的快速进步使生物学家能够产生高维数据以遵循微观水平的生物运动。然而，“感知”现代显微镜的易用性导致了由于在图像采集期间制作的各种不适当的决策而不能支持定量跟踪和分析的子最优数据的挑战。甚至最佳获取的图像通常需要通过数字处理进一步优化在分析之前。在撰写本文时，我们认为我们的目标受众是对数字图像采集和处理的基本理解的生物学家，他们正在寻求理解粒子/物体跟踪实验的基本步骤。考虑到这一目标读者，我们审查了图像处理技术的基本原则以及常用于跟踪实验的分析策略。我们通过对运动行为如何在数学上建模和描述的adisusions结论了这次技术调查。

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