Rao-blackwellized marginal particle filtering for multiple object tracking in molecular bioimaging

Authors:
Ihor Smal;Katharina Draegestein;Niels Galjart;Wiro Niessen;Erik Meijering
Affiliations:
Departments of Radiology and Medical Informatics, University Medical Center Rotterdam, Rotterdam, The Netherlands;Department of Cell Biology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands;Department of Cell Biology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands;Departments of Radiology and Medical Informatics, University Medical Center Rotterdam, Rotterdam, The Netherlands;Departments of Radiology and Medical Informatics, University Medical Center Rotterdam, Rotterdam, The Netherlands
Venue:
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Year:
2007

Citing 6
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Abstract

Modern live cell fluorescence microscopy imaging systems, used abundantly for studying intra-cellular processes in vivo, generate vast amounts of noisy image data that cannot be processed efficiently and accurately by means of manual or current computerized techniques. We propose an improved tracking method, built within a Bayesian probabilistic framework, which better exploits temporal information and prior knowledge. Experiments on simulated and real fluorescence microscopy image data acquired for microtubule dynamics studies show that the technique is more robust to noise, photobleaching, and object interaction than common tracking methods and yields results that are in good agreement with expert cell biologists.