Article

An active particle-based tracking framework for 2D and 3D time-lapse microscopy images.

Centre for Image Processing and Analysis, Dublin City University, Glasnevin, Dublin 9, Ireland.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:6613-8. DOI:10.1109/IEMBS.2011.6091631 pp.6613-8
Source: PubMed

ABSTRACT The process required to track cellular structures is a key task in the study of cell migration. This allows the accurate estimation of motility indicators that help in the understanding of mechanisms behind various biological processes. This paper reports a particle-based fully automatic tracking framework that is able to quantify the motility of living cells in time-lapse images. Contrary to the standard tracking methods based on predefined motion models, in this paper we reformulate the tracking mechanism as a data driven optimization process to remove its reliance on a priory motion models. The proposed method has been evaluated using 2D and 3D deconvolved epifluorescent in-vivo image sequences that describe the development of the quail embryo.

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Keywords

3D deconvolved epifluorescent in-vivo image sequences
 
accurate estimation
 
cell migration
 
motility indicators
 
predefined motion models
 
priory motion models
 
time-lapse images
 
track cellular structures
 
tracking mechanism
 
various biological processes