Our methods described here combined LLS microscopy with image processing and mathematical computing techniques, and our results demonstrated the great potential of this approach. However, before its application in the analysis of other novel molecular mechanisms, we need to improve our automated tracking and image processing techniques. Most importantly for our purpose, improved accuracy of EB1-GFP comet detection is critical. In the case of EB1-GFP detection, one effective way would be the expansion of a 2-D template matching method described by Matov et al.32 to 3-D space, using the average EB1-comet shape. In addition, because the automatic detection algorithm is sensitive to both specimen drift and variations in image intensity, methods that enable highly precise drift correction and image intensity equalization over time and in 3-D space are required for most applications. Changes in image intensity can be caused both by fluctuations in the excitation light intensity and by fluctuations in the distance of an object from the light source (i.e., depth within the specimen). Simple intensity equalization of a whole volume, such as that used in this study, is not sufficient for accurate and complete automatic detection. Indeed, some weak signals within the specimen that were furthermost from the light source or were most aberrated by the cell body were not detected by our analysis. We, therefore, need to develop a technique that can compensate for a three-dimensionally distributed intensity gradient within a specimen and optical heterogeneities within the specimen.