Identifying fusion events in fluorescence microscopy images

We are investigating the dynamical relationships exhibited by virus particles via fluorescence time-lapse microscopy. To obtain a quantitative description of each particle over time, these objects are tracked. To derive an explicit characterization of each particle as well as to identify interesting transient behaviors, the intensity over time of each particle needs to be analyzed. We have developed an approach based on hybrid stochastic systems for identifying behaviors of interest. We employ a hybrid particle filter for estimating the behavior of individual particles. The approach has been successfully applied to particles tracked in synthetic image sequences as well as in real image sequences displaying HIV-1 particles.