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Rapid and Automated Analysis of Portable Flow Cytometer Data

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Recent Developments in Mechatronics and Intelligent Robotics (ICMIR 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 691))

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Abstract

The advent of mass portable cytometry has lead to an unprecedented increase demand for the automated platform of data analysis. To provide a practical method applied to portable devices, we propose a rapid and accurate approach. This approach, based on K-means, initializes the number of clustering using kernel density estimation and optimizes calculation efficiency with k-d tree. After merging by a two-segment line regression algorithm, the clustering groups closest to the true populations can be achieved. Two different experiments proved the method we proposed would provide a rapid and accurate analysis of the multidimensional data of portable flow cytometers.

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Authors and Affiliations

  1. Institute for Drug and Instrument Control of Directorate of Medical Services, Logistics Support Department of Central Military Commission, Beijing, China

    Xianwen Wang, Jianggang Wu, Qingyong Zhang, Xiaoliang Li, Zhiqiang Yang & Li Li

  2. Institute of Health Service and Medical Information, Academy of Military Medical Sciences, Beijing, China

    Peng Li

Authors
  1. Xianwen Wang
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  2. Peng Li
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  3. Jianggang Wu
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  4. Qingyong Zhang
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  5. Xiaoliang Li
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  6. Zhiqiang Yang
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  7. Li Li
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Corresponding author

Correspondence to Li Li .

Editor information

Editors and Affiliations

  1. Shenyang Jianzhu University , Shenyang, China

    Feng Qiao

  2. SOA University , Bhubaneswar, India

    Srikanta Patnaik

  3. Montclair State University , Montclair, New Jersey, USA

    John Wang

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Wang, X. et al. (2018). Rapid and Automated Analysis of Portable Flow Cytometer Data. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 691. Springer, Cham. https://doi.org/10.1007/978-3-319-70990-1_65

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  • DOI: https://doi.org/10.1007/978-3-319-70990-1_65

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70989-5

  • Online ISBN: 978-3-319-70990-1

  • eBook Packages: EngineeringEngineering (R0)

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