Tracking multiple interacting subcellular structure by sequential Monte Carlo method. (24th June 2009)

• Record Type: Journal Article
• Authors: Wen, Quan; Luby-Phelps, Kate; Gao, Jean
• Is Part Of: International journal of data mining and bioinformatics. Volume 3:Number 3(2009)
• Page Start: 314
• Page End: 332
• Publication Date: 2009-06-24
• Subjects: subcellular structure tracking -- SMC -- sequential Monte Carlo -- RJMCMC -- reversible jump Markov chain Monte Carlo -- bioinformatics -- green fluorescent proteins -- GFP -- multiple interacting object tracking -- image sequences; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

With the wide application of Green Fluorescent Proteins (GFP) in the study of live cells, there is a surging need for computer-aided analysis on the huge amount of image sequence data acquired by the advanced microscopy devices. In this paper, a framework based on Sequential Monte Carlo (SMC) is proposed for multiple interacting object tracking. The distribution of the dimension varying joint state is sampled efficiently by a Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm with a novel height swap move. Experimental results were performed on synthetic and real confocal microscopy image sequences.