Literature DB >> 25467412

Development of an automated asbestos counting software based on fluorescence microscopy.

Maxym Alexandrov1, Etsuko Ichida, Tomoki Nishimura, Kousuke Aoki, Takenori Ishida, Ryuichi Hirota, Takeshi Ikeda, Tetsuo Kawasaki, Akio Kuroda.   

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.

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Year:  2014        PMID: 25467412     DOI: 10.1007/s10661-014-4166-y

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  10 in total

Review 1.  Measurement of airborne fibers: a review.

Authors:  P A Baron
Journal:  Ind Health       Date:  2001-04       Impact factor: 2.179

2.  Detection of chrysotile asbestos by using a chrysotile-binding protein.

Authors:  Akio Kuroda; Tomoki Nishimura; Takenori Ishida; Ryuichi Hirota; Kazutaka Nomura
Journal:  Biotechnol Bioeng       Date:  2008-02-01       Impact factor: 4.530

3.  Selective detection of airborne asbestos fibers using protein-based fluorescent probes.

Authors:  Takenori Ishida; Maxym Alexandrov; Tomoki Nishimura; Kenji Minakawa; Ryuichi Hirota; Kiyoshi Sekiguchi; Norihiko Kohyama; Akio Kuroda
Journal:  Environ Sci Technol       Date:  2010-01-15       Impact factor: 9.028

4.  Evaluation of sensitivity of fluorescence-based asbestos detection by correlative microscopy.

Authors:  Takenori Ishida; Maxym Alexandrov; Tomoki Nishimura; Kenji Minakawa; Ryuichi Hirota; Kiyoshi Sekiguchi; Norihiko Kohyama; Akio Kuroda
Journal:  J Fluoresc       Date:  2011-09-21       Impact factor: 2.217

5.  Identification and counting of asbestos fibers.

Authors:  D G Taylor; P A Baron; S A Shulman; J W Carter
Journal:  Am Ind Hyg Assoc J       Date:  1984-02

6.  Asbestos fibre counting by image analysis--the performance of the Manchester Asbestos Program on Magiscan.

Authors:  L C Kenny
Journal:  Ann Occup Hyg       Date:  1984

7.  Asbestos: scientific developments and implications for public policy.

Authors:  B T Mossman; J Bignon; M Corn; A Seaton; J B Gee
Journal:  Science       Date:  1990-01-19       Impact factor: 47.728

8.  Mass and number of fibres in the pathogenesis of asbestos-related lung disease in rats.

Authors:  J M Davis; S T Beckett; R E Bolton; P Collings; A P Middleton
Journal:  Br J Cancer       Date:  1978-05       Impact factor: 7.640

9.  Selective detection and automated counting of fluorescently-labeled chrysotile asbestos using a dual-mode high-throughput microscopy (DM-HTM) method.

Authors:  Myoung-Ock Cho; Hyo Mi Chang; Donghee Lee; Yeon Gyu Yu; Hwataik Han; Jung Kyung Kim
Journal:  Sensors (Basel)       Date:  2013-05-02       Impact factor: 3.576

10.  Molecular engineering of a fluorescent bioprobe for sensitive and selective detection of amphibole asbestos.

Authors:  Takenori Ishida; Maxym Alexandrov; Tomoki Nishimura; Ryuichi Hirota; Takeshi Ikeda; Akio Kuroda
Journal:  PLoS One       Date:  2013-09-27       Impact factor: 3.240

  10 in total

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