Development of an automated asbestos counting software based on fluorescence microscopy

  • Maxym Alexandrov
  • Etsuko Ichida
  • Tomoki Nishimura
  • Kousuke Aoki
  • Takenori Ishida
  • Ryuichi Hirota
  • Takeshi Ikeda
  • Tetsuo Kawasaki
  • Akio Kuroda
Article

Abstract

An emerging alternative to the commonly used analytical methods for asbestos analysis is fluorescence microscopy (FM), which relies on highly specific asbestos-binding probes to distinguish asbestos from interfering non-asbestos fibers. However, all types of microscopic asbestos analysis require laborious examination of large number of fields of view and are prone to subjective errors and large variability between asbestos counts by different analysts and laboratories. A possible solution to these problems is automated counting of asbestos fibers by image analysis software, which would lower the cost and increase the reliability of asbestos testing. This study seeks to develop a fiber recognition and counting software for FM-based asbestos analysis. We discuss the main features of the developed software and the results of its testing. Software testing showed good correlation between automated and manual counts for the samples with medium and high fiber concentrations. At low fiber concentrations, the automated counts were less accurate, leading us to implement correction mode for automated counts. While the full automation of asbestos analysis would require further improvements in accuracy of fiber identification, the developed software could already assist professional asbestos analysts and record detailed fiber dimensions for the use in epidemiological research.

Keywords

Automated asbestos counting software Fluorescence microscopy Asbestos fibers 

Notes

Acknowledgments

This work was supported by the Development of Systems and Technology for Advanced Measurement and Analysis Program of the Japan Science and Technology Agency. The sample collection was partially supported by the Ministry of the Environment, Japan, through the Environment Research and Technology Development Fund (5-1401).

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Maxym Alexandrov
    • 1
  • Etsuko Ichida
    • 2
  • Tomoki Nishimura
    • 1
  • Kousuke Aoki
    • 2
  • Takenori Ishida
    • 1
  • Ryuichi Hirota
    • 1
  • Takeshi Ikeda
    • 1
  • Tetsuo Kawasaki
    • 2
  • Akio Kuroda
    • 1
  1. 1.Department of Molecular Biotechnology, Graduate School of Advanced Sciences of MatterHiroshima UniversityHigashi HiroshimaJapan
  2. 2.Advanced Technology Research and Development InstituteINTEC Inc.YokohamaJapan

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