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http://dx.doi.org/10.5407/JKSV.2015.13.3.015

Improvement of Image Processing Algorithm of High-Throughput Microscopy for Automated Counting of Asbestos Fibers  

Cho, Myoung-Ock (국민대학교 기계공학과)
Yoon, Seonghee (국민대학교 기계공학과)
Han, Hwataik (국민대학교 기계공학과)
Kim, Jung Kyung (국민대학교 기계공학과)
Publication Information
Journal of the Korean Society of Visualization / v.13, no.3, 2015 , pp. 15-19 More about this Journal
Abstract
We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.
Keywords
Asbestos; PCM; HTM; Image analysis; Variable parameters;
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Times Cited By KSCI : 1  (Citation Analysis)
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