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June 2015 Tracking rapid intracellular movements: A Bayesian random set approach
Vasileios Maroulas, Andreas Nebenführ
Ann. Appl. Stat. 9(2): 926-949 (June 2015). DOI: 10.1214/15-AOAS819

Abstract

We focus on the biological problem of tracking organelles as they move through cells. In the past, most intracellular movements were recorded manually, however, the results are too incomplete to capture the full complexity of organelle motions. An automated tracking algorithm promises to provide a complete analysis of noisy microscopy data. In this paper, we adopt statistical techniques from a Bayesian random set point of view. Instead of considering each individual organelle, we examine a random set whose members are the organelle states and we establish a Bayesian filtering algorithm involving such set states. The propagated multi-object densities are approximated using a Gaussian mixture scheme. Our algorithm is applied to synthetic and experimental data.

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Vasileios Maroulas. Andreas Nebenführ. "Tracking rapid intracellular movements: A Bayesian random set approach." Ann. Appl. Stat. 9 (2) 926 - 949, June 2015. https://doi.org/10.1214/15-AOAS819

Information

Received: 1 September 2013; Revised: 1 December 2014; Published: June 2015
First available in Project Euclid: 20 July 2015

zbMATH: 06499937
MathSciNet: MR3371342
Digital Object Identifier: 10.1214/15-AOAS819

Keywords: cardinalized probability hypothesis density , finite set statistics , Gaussian mixture implementation , monitoring intracellular movements , Multi-object Bayesian filtering , random finite set theory

Rights: Copyright © 2015 Institute of Mathematical Statistics

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Vol.9 • No. 2 • June 2015
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