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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2011
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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. |
format | Online Article Text |
id | pubmed-3231659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
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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