Cell automatic tracking technique with particle filter

Authors:
Mingli Lu;Benlian Xu;Andong Sheng
Affiliations:
School of Automation, Nanjing University of Science & Technology, Nanjing, China,School of Electrical & Automatic Engineering, Changshu Institute of Technology, Changshu, China;School of Electrical & Automatic Engineering, Changshu Institute of Technology, Changshu, China;School of Automation, Nanjing University of Science & Technology, Nanjing, China
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Year:
2012

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Abstract

Cell motion analysis contributes to research the mechanism of the inflammatory process and to the development of anti-inflammatory drugs. To gain full dynamics of multiple cells, a hybrid cell detection algorithm is first designed, which is combined with several methods, such as threshold processing, distance transform, watershed negative transform, and shape and boundary constraint, to reduce over-segmentation and contour missing. By exploiting temporal information and prior knowledge, a particle-filter-based tracking technique is then proposed for image sequences to estimate individual state of multiple cells. Simulation results are presented to support obtained favorable performance of our algorithm.