Microtubule dynamics analysis using kymographs and variable-rate particle filters

Authors:
Ihor Smal;Ilya Grigoriev;Anna Akhmanova;Wiro J. Niessen;Erik Meijering
Affiliations:
Departments of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands;Department of Cell Biology, Erasmus MC, Rotterdam, The Netherlands;Department of Cell Biology, Erasmus MC, Rotterdam, The Netherlands;Departments of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands and Department of Imaging Science & Technology, Delft University of Technology, Delft, The Netherlands;Departments of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
Venue:
IEEE Transactions on Image Processing
Year:
2010

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Abstract

Studying intracellular dynamics is of fundamental importance for understanding healthy life at the molecular level and for developing drugs to target disease processes. One of the key technologies to enable this research is the automated tracking and motion analysis of these objects in microscopy image sequences. To make better use of the spatiotemporal information than common frame-by-frame tracking methods, two alternative approaches have recently been proposed, based upon either Bayesian estimation or space-time segmentation. In this paper, we propose to combine the power of both approaches, and develop a new probabilistic method to segment the traces of the moving objects in kymograph representations of the image data. It is based on variable-rate particle filtering and uses multiscale trend analysis of the extracted traces to estimate the relevant kinematic parameters. Experiments on realistic synthetically generated images as well as on real biological image data demonstrate the improved potential of the new method for the analysis of microtubule dynamics in vitro.