Tracking single particles: a user-friendly quantitative evaluation
Tracking single particles: a user-friendly quantitative evaluation
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DOI：
10.1088/1478-3967/2/1/008
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发表时间：
2005-03-01
期刊：
影响因子：
2
通讯作者：
Gross, SP
中科院分区：
文献类型：
--
作者：
Carter, BC;Shubeita, GT;Gross, SP
随着我们对生物过程知识的进步，我们越来越意识到细胞主动定位亚细胞细胞器和其他成分来控制广泛的生物过程。许多研究量化的位置和运动，例如，荧光标记的蛋白质，蛋白质聚集体，mRNA颗粒或病毒颗粒。差示干涉对比（DIC）和荧光显微镜都能观察到细胞内运动的囊泡、细胞核或其他小细胞器。虽然这类研究越来越重要，但目前还没有对使用的不同跟踪方法进行完整的分析，特别是从实际的角度来看。在这里，我们研究了这些方法，并阐明了不同算法的工作效果，以及哪些因素在评估物体位置的准确性方面发挥了作用。具体来说，我们考虑了放大倍率、摄像机类型（模拟与数字）、记录介质（VHS和SVHS磁带与摄像机直接跟踪）、图像压缩、所用成像类型（荧光与DIC图像）以及各种噪声源对最终性能的影响。结果表明，大多数方法在实际条件下具有纳米级精度；跟踪精度随噪声的增大而降低。令人惊讶的是，精度被发现对数值孔径不敏感，但是，正如预期的那样，它与放大倍率有关，更高的放大倍率产生更高的精度（在信噪比限制内）。当噪声处于合理水平时，大多数情况下图像压缩的效果很小。最后，我们提供了一个免费的、健壮的跟踪算法实现，它很容易下载和安装。
As our knowledge of biological processes advances, we are increasingly aware that cells actively position sub-cellular organelles and other constituents to control a wide range of biological processes. Many studies quantify the position and motion of, for example, fluorescently labeled proteins, protein aggregates, mRNA particles or virus particles. Both differential interference contrast (DIC) and fluorescence microscopy can visualize vesicles, nuclei or other small organelles moving inside cells. While such studies are increasingly important, there has been no complete analysis of the different tracking methods in use, especially from the practical point of view. Here we investigate these methods and clarify how well different algorithms work and also which factors play a role in assessing how accurately the position of an object can be determined. Specifically, we consider how ultimate performance is affected by magnification, by camera type ( analog versus digital), by recording medium (VHS and SVHS tape versus direct tracking from camera), by image compression, by type of imaging used (fluorescence versus DIC images) and by a variety of sources of noise. We show that most methods are capable of nanometer scale accuracy under realistic conditions; tracking accuracy decreases with increasing noise. Surprisingly, accuracy is found to be insensitive to the numerical aperture, but, as expected, it scales with magnification, with higher magnification yielding improved accuracy (within limits of signal-to-noise). When noise is present at reasonable levels, the effect of image compression is in most cases small. Finally, we provide a free, robust implementation of a tracking algorithm that is easily downloaded and installed.