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Model Dependency of RBMCDA for Tracking Multiple Targets in Fluorescence Microscopy

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Bildverarbeitung für die Medizin 2012

Part of the book series: Informatik aktuell ((INFORMAT))

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Abstract

The analysis of the dynamics of sub-cellular structures is of great interest to bio-medical research. We propose to use probabilistic tracking techniques to analyze the dynamics of stress granules (SGs) to avoid the problems of manual analysis. A crucial challenge in multitarget tracking is the association of observations to underlying targets. Rao-Blackwellized Monte Carlo Data Association (RBMCDA) based on sampling of association variables avoids the combinatorics of this association problem. We propose the use of a parametric data association prior for sampling of association variables and evaluate tracking results with regard to the impact of parameter deviations on synthetic data.

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Correspondence to Oliver Greß .

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© 2012 Springer-Verlag Berlin Heidelberg

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Greß, O., Posch, S. (2012). Model Dependency of RBMCDA for Tracking Multiple Targets in Fluorescence Microscopy. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2012. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28502-8_44

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