Abstract
Time-lapse imaging is a rich data source offering potential kinetic information of cellular activity and behavior. Tracking and extracting measurements of objects from time-lapse datasets are challenges that result from the complexity and dynamics of each object's motion and intensity or the appearance of new objects in the field of view. A wide range of strategies for proper data sampling, object detection, image analysis, and post-analysis interpretation are available. Theory and methods for single-particle tracking, spot detection, and object linking are discussed in this unit, as well as examples with step-by-step procedures for utilizing semi-automated software and visualization tools for achieving tracking results and interpreting this output.
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