An adaptive statistical test to detect non Brownian diffusion from particle trajectories

Vincent Briane (1, 2) , Myriam Vimond (2) , Charles Kervrann (1)

1 SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes
2 CREST - Centre de Recherche en Economie et Statistique [Bruz]

Assessing the dynamics of particles inside live cell is of paramount interest to understand cell mechanisms. In this paper, we assume that the motions of particles follow a certain class of random process: the diffusion processes. Our contribution is to propose a statistical method able to classify the motion of the observed trajectories into three groups: confined, directed and free diffusion (namely Brownian motion). This method is an alternative to Mean Square Displacement (MSD) analysis. We assess our procedure on both simulations and real cases.

Mots clés: trajectory; tracking; diffusion; classification; statistical test

Domaines: Traitement des images [eess.IV]; Statistiques [math.ST]; Biologie cellulaire

Vincent Briane, Myriam Vimond, Charles Kervrann. An adaptive statistical test to detect non Brownian diffusion from particle trajectories. Workshop SSIAB - Spatial Statistics and Image Analysis in Biology, May 2016, Rennes, France. ⟨hal-01416812⟩