TRACKING RAPID INTRACELLULAR MOVEMENTS: A BAYESIAN RANDOM SET APPROACH

• 成果类型: Article
• 署名作者: Maroulas, Vasileios; Nebenfuehr, Andreas
• 署名单位: University of Tennessee System; University of Tennessee Knoxville; University of Tennessee System; University of Tennessee Knoxville
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/15-AOAS819
• 发表日期: 2015
• 页码: 926-949
• 关键词: golgi stacks; xi-k; mitochondria; actin; TRAFFICKING; arabidopsis; peroxisomes; inference; images; cells

摘要

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.