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

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

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...

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Bibliographic Details
Published in:2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) pp. 972 - 975
Main Authors: Briane, V., Vimond, M., Kervrann, C.
Format: Conference Proceeding Journal Article
Language:English
Published: IEEE 01-04-2016
Subjects:
Brownian motion
Classification
Diffusion
Diffusion processes
Dynamic tests
Estimation
Force
mean square displacement
Mean square values
Particle trajectories
Probability
Sections
Simulation
statistical test
Statistical tests
Stochastic processes
Trajectory
trajectory classification
Online Access:Get full text
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Summary: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.
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SourceType-Conference Papers & Proceedings-2
ISSN:1945-8452
DOI:10.1109/ISBI.2016.7493427