We present an algorithm for the three-dimensional (3D) tracking of multiple fluorescent subresolution tags with super-resolution in images of living cells. Recently, we described an algorithm for the automatic detection of such tags in single flames and demonstrated its potential in a biological system. The algorithm presented here adds to the tag detector a module for relative tracking of the signals between frames. As with tag detection, the main problem in relative tracking arises when signals of multiple tags interfere. We propose a novel multitemplate matching framework that exploits knowledge of the microscope point spread function to separate the intensity contribution of each tag in image regions with signal interferences. We use this intensity splitting to reconstruct a template for each tag in the source frame and a patch in the target frame, which are both free of intensity contributions from other tag signals. Tag movements between flames are then tracked by seeking, for each template-patch pair, the displacement vector providing the best signal match in terms of the sum of squared intensity differences. Because template and patch generation of tags with overlapping signals are interdependent, the matching is carried out simultaneously for all tags, and in an iterative manner. We have examined the performance of our approach using synthetic 3D data and observed a significant increase in resolution and robustness as compared with our previously described detector. It is now possible to localize and track tags separated by a distance three times smaller than the Rayleigh limit with a relative positional accuracy of better than 50 nm. We have applied the new tracking system to extract metaphase trajectories of fluorescently tagged chromosomes relative to the spindle poles in budding yeast.
- Computer vision
- GFP tags
ASJC Scopus subject areas
- Pathology and Forensic Medicine