Quantitative comparison of algorithms for tracking single fluorescent particles
Quantitative comparison of algorithms for tracking single fluorescent particles
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DOI：
10.1016/s0006-3495(01)75884-5
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发表时间：
2001-10-01
影响因子：
3.4
通讯作者：
Guilford, WH
中科院分区：
文献类型：
--
作者：
Cheezum, MK;Walker, WF;Guilford, WH
单粒子跟踪在生物物理学中有许多应用，从细胞膜中蛋白质的扩散到分子马达的运动。已经开发了大量的计算机算法来监测连续视频帧之间荧光物体的亚像素位移，并且一些算法已经声称具有“纳米”分辨率。到目前为止，还没有严格的比较，这些算法在现实条件下。在本文中，我们定量地比较了四种常用的跟踪算法的具体实现：互相关，和绝对差，质心，直接高斯拟合。用已知的亚像素位移，计算机生成的荧光物体的图像的大小范围从点源到5妈妈。添加真实噪声，并比较上述四种算法的准确度和精度。我们发现，互相关是大颗粒的最准确的算法。然而，对于点源，直接高斯拟合的强度分布是上级算法的准确性和精度方面，是最强大的在低信噪比。最重要的是，当信噪比接近4时，所有四种算法都失败了。我们判断直接高斯拟合是最好的算法时，跟踪单个荧光团，其中的信号噪声往往接近4。
Single particle tracking has seen numerous applications in biophysics, ranging from the diffusion of proteins in cell membranes to the movement of molecular motors. A plethora of computer algorithms have been developed to monitor the sub-pixel displacement of fluorescent objects between successive video frames, and some have been claimed to have "nanometer" resolution. To date, there has been no rigorous comparison of these algorithms under realistic conditions. In this paper, we quantitatively compare specific implementations of four commonly used tracking algorithms: cross-correlation, sum-absolute difference, centroid, and direct Gaussian fit. Images of fluorescent objects ranging in size from point sources to 5 mum were computer generated with known sub-pixel displacements. Realistic noise was added and the above four algorithms were compared for accuracy and precision. We found that cross-correlation is the most accurate algorithm for large particles. However, for point sources, direct Gaussian fit to the intensity distribution is the superior algorithm in terms of both accuracy and precision, and is the most robust at low signal-to-noise. Most significantly, all four algorithms fail as the signal-to-noise ratio approaches 4. We judge direct Gaussian fit to be the best algorithm when tracking single fluorophores, where the signal-to-noise is frequently near 4.