Quantitative inference of bacterial motility behavior

Xiaomeng Liang, Lin Ching Chang, Arash Massoudieh, Nanxi Lu, Thanh H. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a framework for automatic bacteria motile trajectories detection and motility behavior clustering. The input data is a sequence of images which contains bacteria motility information. The traditional experimental methods to identify the trajectories, and segment them to "run" and "tumble" modes are time consuming and subjective. The proposed method processes bacteria motility movies and extracts statistical features of runs and tumbles which drastically saves time, human labor, and minimizes human error. The statistics will be used in simulations to model bacteria motility. The methodology can be replicated with similar format of experimental microscopic images.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015
EditorsQuoc-Nam Tran, Leonidas Deligiannidis, Hamid R. Arabnia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages368-373
Number of pages6
ISBN (Electronic)9781467397957
DOIs
StatePublished - Mar 2 2016
EventInternational Conference on Computational Science and Computational Intelligence, CSCI 2015 - Las Vegas, United States
Duration: Dec 7 2015Dec 9 2015

Publication series

NameProceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015

Other

OtherInternational Conference on Computational Science and Computational Intelligence, CSCI 2015
CountryUnited States
CityLas Vegas
Period12/7/1512/9/15

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Keywords

  • Bacteria motility
  • Image processing
  • Pattern recognition
  • Trajectories detection

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

Cite this

Liang, X., Chang, L. C., Massoudieh, A., Lu, N., & Nguyen, T. H. (2016). Quantitative inference of bacterial motility behavior. In Q-N. Tran, L. Deligiannidis, & H. R. Arabnia (Eds.), Proceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015 (pp. 368-373). [7424119] (Proceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI.2015.97