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Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method

Inhalation of airborne asbestos causes serious health problems such as lung cancer and malignant mesothelioma. The phase-contrast microscopy (PCM) method has been widely used for estimating airborne asbestos concentrations because it does not require complicated processes or high-priced equipment. H...

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Autores principales: Cho, Myoung-Ock, Yoon, Seonghee, Han, Hwataik, Kim, Jung Kyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231659/
https://www.ncbi.nlm.nih.gov/pubmed/22164014
http://dx.doi.org/10.3390/s110707231
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author Cho, Myoung-Ock
Yoon, Seonghee
Han, Hwataik
Kim, Jung Kyung
author_facet Cho, Myoung-Ock
Yoon, Seonghee
Han, Hwataik
Kim, Jung Kyung
author_sort Cho, Myoung-Ock
collection PubMed
description Inhalation of airborne asbestos causes serious health problems such as lung cancer and malignant mesothelioma. The phase-contrast microscopy (PCM) method has been widely used for estimating airborne asbestos concentrations because it does not require complicated processes or high-priced equipment. However, the PCM method is time-consuming and laborious as it is manually performed off-site by an expert. We have developed a high-throughput microscopy (HTM) method that can detect fibers distinguishable from other spherical particles in a sample slide by image processing both automatically and quantitatively. A set of parameters for processing and analysis of asbestos fiber images was adjusted for standard asbestos samples with known concentrations. We analyzed sample slides containing airborne asbestos fibers collected at 11 different workplaces following PCM and HTM methods, and found a reasonably good agreement in the asbestos concentration. Image acquisition synchronized with the movement of the robotic sample stages followed by an automated batch processing of a stack of sample images enabled us to count asbestos fibers with greatly reduced time and labors. HTM should be a potential alternative to conventional PCM, moving a step closer to realization of on-site monitoring of asbestos fibers in air.
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spelling pubmed-32316592011-12-07 Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method Cho, Myoung-Ock Yoon, Seonghee Han, Hwataik Kim, Jung Kyung Sensors (Basel) Article Inhalation of airborne asbestos causes serious health problems such as lung cancer and malignant mesothelioma. The phase-contrast microscopy (PCM) method has been widely used for estimating airborne asbestos concentrations because it does not require complicated processes or high-priced equipment. However, the PCM method is time-consuming and laborious as it is manually performed off-site by an expert. We have developed a high-throughput microscopy (HTM) method that can detect fibers distinguishable from other spherical particles in a sample slide by image processing both automatically and quantitatively. A set of parameters for processing and analysis of asbestos fiber images was adjusted for standard asbestos samples with known concentrations. We analyzed sample slides containing airborne asbestos fibers collected at 11 different workplaces following PCM and HTM methods, and found a reasonably good agreement in the asbestos concentration. Image acquisition synchronized with the movement of the robotic sample stages followed by an automated batch processing of a stack of sample images enabled us to count asbestos fibers with greatly reduced time and labors. HTM should be a potential alternative to conventional PCM, moving a step closer to realization of on-site monitoring of asbestos fibers in air. Molecular Diversity Preservation International (MDPI) 2011-07-18 /pmc/articles/PMC3231659/ /pubmed/22164014 http://dx.doi.org/10.3390/s110707231 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Cho, Myoung-Ock
Yoon, Seonghee
Han, Hwataik
Kim, Jung Kyung
Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method
title Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method
title_full Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method
title_fullStr Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method
title_full_unstemmed Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method
title_short Automated Counting of Airborne Asbestos Fibers by a High-Throughput Microscopy (HTM) Method
title_sort automated counting of airborne asbestos fibers by a high-throughput microscopy (htm) method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231659/
https://www.ncbi.nlm.nih.gov/pubmed/22164014
http://dx.doi.org/10.3390/s110707231
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