Single-particle tracking (SPT) is a range of powerful analysis techniques that measure particle motion from video microscopy image sequences. SPT is used to study the behavior of motor proteins and associated organelle transport within a cell. Many SPT algorithms deliver subpixel accurate measurements with noisy data corresponding to sub-10-nm resolution. Image-correlation techniques have been shown to be the most accurate method of tracking extended objects. However, to date, it has not been possible to determine the level of error when measuring the motion of an arbitrary particle with this method. In this article we derive a method for experimentally determining the accuracy of image-correlation-based SPT. We then apply this technique to a series of confocal fluorescence microscope image sequences of mitochondria, demonstrating the possibility of making measurements accurate to 5 nm when working with extended objects within live cells. In doing so we show that for particles with a low signal/noise ratio, the accuracy can vary by a factor of 2, corresponding to different particle shapes for a given signal/noise ratio. Use of the presented technique will allow researchers to quantify the accuracy of their measurements on a per-particle basis. This in turn will allow the selection of the most accurately tracked particles, helping to push the accuracy of spatial measurements well below the diffraction limit. This is particularly important for the study of molecular motors whose step size is a similar scale to these limits.
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