Cell tracking under high confluency conditions by candidate cell region detection-based association approach

Ryoma Bise, Yoshitaka Maeda, Mee Hae Kim, Masahiro Kino-Oka

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

2 Citations (Scopus)

Abstract

Automated tracking of cell population is an important element of research and discovery in the biology field. In this paper, we propose a method that tracks cells under highly confluent conditions by using the candidate cell region detection-based association approach. Unlike conventional segmentation-based association tracking methods, the proposed method uses the tracking results from the previous frame to segment the cell regions at the current frame. First, candidate cell regions are detected, and while there may be many false positives, there are very few false negatives. Next, optimized detection results are selected from the candidate regions and associated with the tracking results of the previous frame by resolving a linear programming problem. We quantitatively evaluated the proposed method using a variety of sequences. Results showed that our method has a better tracking performance than conventional segmentation-based association methods.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013
Pages554-561
Number of pages8
DOIs
Publication statusPublished - 2013
Event10th IASTED International Conference on Biomedical Engineering, BioMed 2013 - Innsbruck, Austria
Duration: Feb 13 2013Feb 15 2013

Publication series

NameProceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013

Other

Other10th IASTED International Conference on Biomedical Engineering, BioMed 2013
CountryAustria
CityInnsbruck
Period2/13/132/15/13

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

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  • Cite this

    Bise, R., Maeda, Y., Kim, M. H., & Kino-Oka, M. (2013). Cell tracking under high confluency conditions by candidate cell region detection-based association approach. In Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013 (pp. 554-561). (Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013). https://doi.org/10.2316/P.2013.791-057