Tracking Virus Particles in Microscopy Images Using Multi-Frame Association

Astha Jaiswal, William J. Godinez, Roland Eils, Maik Jörg Lehmann, Karl Rohr

Abstract: Automatic tracking of fluorescent particles is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic tracking approach based on multi-frame association finding and the Kalman filter. We have successfully applied the approach to synthetic as well as real microscopy image sequences of ALV virus particles and have performed a quantitative comparison with previous approaches.