Particle Filtering for Multiple Object Tracking in Molecular Cell Biology

Abstract

Motion analysis of subcellular structures in living cells is currently a major topic in molecular cell biology, for which computerized methods are desperately needed. In this paper we adopt and tailor particle filtering techniques for this purpose and present the results of robust and accurate tracking of multiple objects in real fluorescence microscopy image data acquired for specific biological studies. Experimental results demonstrate that the automated method produces results comparable to manual tracking but using only a fraction of the manual tracking time.