A novel approach to identifying merging/splitting events in time-lapse microscopy

This paper investigates the complex motion of particles in the endocytic pathway. We propose a novel tracking method, which identifies merging and splitting events of vesicles, in dual channel fluorescence confocal microscopy. Large amounts of quantitative data are needed for biologists to make sound conclusions about cellular dynamics. Having an automated method also allows biologists to identify rare events, which would otherwise be very time consuming. A co-localisation state is introduced to identify when vesicles are merged, across two channels. The approach is based on a probabilistic association between estimated vesicle states in each channel. We incorporate this into a reversible jump Markov chain Monte Carlo scheme. The approach has been successfully applied to synthetic videos as well as real data.