Counting-based particle flux estimation for traffic analysis in live cell imaging
IEEE Journal of Selected Topics in Signal Processing (Special issue on Advanced Signal Processing in Microscopy and Cell Imaging)
Authors: T. Pécot, C. Kervrann, J. Salamero, J. Boulanger Date: 2016-02-01 • Pages: 203-216 • DOI: 10.1109/JSTSP.2015.2482460 Article URL: https://hal.inria.fr/hal-01244946
A quantitative analysis of the dynamic contents in fluorescence time-lapse microscopy is crucial to decipher the molecular mechanisms involved in cell functions. In this paper, we propose an original traffic analysis approach based on the counting of particles from frame to frame. The suggested method lies between individual object tracking and dense motion estimation (i.e., optical flow). Instead of tracking each moving particle, we estimate fluxes of particles between predefined and adjacent regions. The problem is formulated as the minimization of a global cost function and the approach allows us to process image sequences with a high number of particles and a high rate of particle appearances and disappearances. We propose to study the influence of object density, image partition scale, motion amplitude, and particle appearances/disappearances in a large variety of simulations. The potential of the method is finally demonstrated on real image sequences showing GFP-tagged Rab6 trafficking in confocal microscopy.