The Annals of Applied Statistics

Tracking rapid intracellular movements: A Bayesian random set approach

Vasileios Maroulas and Andreas Nebenführ

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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.

Article information

Source
Ann. Appl. Stat. Volume 9, Number 2 (2015), 926-949.

Dates
Received: September 2013
Revised: December 2014
First available in Project Euclid: 20 July 2015

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1437397118

Digital Object Identifier
doi:10.1214/15-AOAS819

Mathematical Reviews number (MathSciNet)
MR3371342

Zentralblatt MATH identifier
06499937

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

Citation

Maroulas, Vasileios; Nebenführ, Andreas. Tracking rapid intracellular movements: A Bayesian random set approach. Ann. Appl. Stat. 9 (2015), no. 2, 926--949. doi:10.1214/15-AOAS819. https://projecteuclid.org/euclid.aoas/1437397118


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