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Cell Automatic Tracking Technique with Particle Filter

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Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7332))

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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.

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References

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Author information

Authors and Affiliations

  1. School of Automation, Nanjing University of Science & Technology, 210094, Nanjing, China

    Mingli Lu & Andong Sheng

  2. School of Electrical & Automatic Engineering, Changshu Institute of Technology, 215500, Changshu, China

    Mingli Lu & Benlian Xu

Authors
  1. Mingli Lu
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  2. Benlian Xu
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  3. Andong Sheng
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Lu, M., Xu, B., Sheng, A. (2012). Cell Automatic Tracking Technique with Particle Filter. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_70

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  • DOI: https://doi.org/10.1007/978-3-642-31020-1_70

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31019-5

  • Online ISBN: 978-3-642-31020-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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