Section: New Results

Estimation of the flow of particles without tracking algorithm in fluorescence imaging

Participants : Thierry Pécot, Patrick Bouthemy, Charles Kervrann.

Figure 13. Vesicle flows estimated with our method when considering a simple partition of 5 regions for an image sequence acquired in TIRF microscopy and showing the protein Clip170.

Automatic analysis of the dynamic content in fluorescence video-microscopy is crucial for understanding molecular mechanisms involved in cell functions. We have proposed an original approach for analyzing particle trafficking in these sequences. Instead of individually tracking every particle, we only need to locally count particles on regions over time and minimize a global energy function. We have specified three methods to determine the particle flow. We especially compared the NNLS algorithm [44] and the PPXA algorithm [33] known as well suited to non differentiable convex minimization problem [24] . We have conducted comparative experiments on synthetic and real fluorescence image sequences. We have shown that adding a sparsity constraint on the number of detected events allows us to reduce the number of false alarms. Compared to usual tracking methods, our approach is simpler and the results are very stable with respect to the only two parameters involved (see Fig. 13 ).

Reference: [24]

Partners: Jean Salamero, J. Boulanger (UMR 144, PICT IBiSA, CNRS-Institut Curie)