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Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging
The polarization imaging technique is a powerful approach to probe microstructural and optical information of biological structures (e.g., tissue samples). Here, we have studied the polarization properties of different bacterial colonies in order to evaluate the possibility of bacterial detection an...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050273/ https://www.ncbi.nlm.nih.gov/pubmed/30018335 http://dx.doi.org/10.1038/s41598-018-29059-5 |
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author | Badieyan, Saeedesadat Dilmaghani-Marand, Arezou Hajipour, Mohammad Javad Ameri, Ali Razzaghi, Mohammad Reza Rafii-Tabar, Hashem Mahmoudi, Morteza Sasanpour, Pezhman |
author_facet | Badieyan, Saeedesadat Dilmaghani-Marand, Arezou Hajipour, Mohammad Javad Ameri, Ali Razzaghi, Mohammad Reza Rafii-Tabar, Hashem Mahmoudi, Morteza Sasanpour, Pezhman |
author_sort | Badieyan, Saeedesadat |
collection | PubMed |
description | The polarization imaging technique is a powerful approach to probe microstructural and optical information of biological structures (e.g., tissue samples). Here, we have studied the polarization properties of different bacterial colonies in order to evaluate the possibility of bacterial detection and discrimination. In this regard, we have taken the backscattering Mueller matrix images of four different bacteria colonies (i.e., Escherichia coli, Lactobacillus rhamnosus, Rhodococcus erythropolis, and Staphylococcus aureus). Although the images have the potential to distinguish qualitatively different bacterial colonies, we explored more accurate and quantitative parameters criteria for discrimination of bacterial samples; more specifically, we have exploited the Mueller matrix polar decomposition (MMPD),frequency distribution histogram (FDH), and central moment analysis method. The outcomes demonstrated a superior capacity of Mueller matrix imaging, MMPD, and FDH in bacterial colonies identification and discrimination. This approach might pave the way for a reliable, efficient, and cheap way of identification of infectious diseases. |
format | Online Article Text |
id | pubmed-6050273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60502732018-07-19 Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging Badieyan, Saeedesadat Dilmaghani-Marand, Arezou Hajipour, Mohammad Javad Ameri, Ali Razzaghi, Mohammad Reza Rafii-Tabar, Hashem Mahmoudi, Morteza Sasanpour, Pezhman Sci Rep Article The polarization imaging technique is a powerful approach to probe microstructural and optical information of biological structures (e.g., tissue samples). Here, we have studied the polarization properties of different bacterial colonies in order to evaluate the possibility of bacterial detection and discrimination. In this regard, we have taken the backscattering Mueller matrix images of four different bacteria colonies (i.e., Escherichia coli, Lactobacillus rhamnosus, Rhodococcus erythropolis, and Staphylococcus aureus). Although the images have the potential to distinguish qualitatively different bacterial colonies, we explored more accurate and quantitative parameters criteria for discrimination of bacterial samples; more specifically, we have exploited the Mueller matrix polar decomposition (MMPD),frequency distribution histogram (FDH), and central moment analysis method. The outcomes demonstrated a superior capacity of Mueller matrix imaging, MMPD, and FDH in bacterial colonies identification and discrimination. This approach might pave the way for a reliable, efficient, and cheap way of identification of infectious diseases. Nature Publishing Group UK 2018-07-17 /pmc/articles/PMC6050273/ /pubmed/30018335 http://dx.doi.org/10.1038/s41598-018-29059-5 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Badieyan, Saeedesadat Dilmaghani-Marand, Arezou Hajipour, Mohammad Javad Ameri, Ali Razzaghi, Mohammad Reza Rafii-Tabar, Hashem Mahmoudi, Morteza Sasanpour, Pezhman Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging |
title | Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging |
title_full | Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging |
title_fullStr | Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging |
title_full_unstemmed | Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging |
title_short | Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging |
title_sort | detection and discrimination of bacterial colonies with mueller matrix imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050273/ https://www.ncbi.nlm.nih.gov/pubmed/30018335 http://dx.doi.org/10.1038/s41598-018-29059-5 |
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