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Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting

Background: Accurate quantitative analysis of microorganisms is recognized as an essential tool for gauging safety and quality in microbiology settings in a wide range of fields. The enumeration process of viable microorganisms via traditional culturing techniques are methodically convenient and cos...

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Autores principales: Rodrigues, Pedro Miguel, Luís, Jorge, Tavaria, Freni Kekhasharú
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9312004/
https://www.ncbi.nlm.nih.gov/pubmed/35877322
http://dx.doi.org/10.3390/bioengineering9070271
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author Rodrigues, Pedro Miguel
Luís, Jorge
Tavaria, Freni Kekhasharú
author_facet Rodrigues, Pedro Miguel
Luís, Jorge
Tavaria, Freni Kekhasharú
author_sort Rodrigues, Pedro Miguel
collection PubMed
description Background: Accurate quantitative analysis of microorganisms is recognized as an essential tool for gauging safety and quality in microbiology settings in a wide range of fields. The enumeration process of viable microorganisms via traditional culturing techniques are methodically convenient and cost-effective, conferring high applicability worldwide. However, manual counting can be time-consuming, laborious and imprecise. Furthermore, particular cases require an urgent and accurate response for effective processing. Methods: To reduce time limitations and discrepancies, this work introduces an image processing method capable of semi-automatically quantifying the number of colony forming units (CFUs). This rapid enumeration technique enables the technician to provide an expeditious assessment of the microbial load of a given sample. To test and validate the system, three bacterial species were cultured, and a labeled database was created, with subsequent image acquisition. Results: The system demonstrated acceptable classification measures; the mean values of Accuracy, Recall and F-measure were: (1) 95%, 95% and 0.95 for E. coli; (2) 91%, 91% and 0.90 for P. aeruginosa; and (3) 84%, 86% and 0.85 for S. aureus. Conclusions: Evidence related to the time-saving potential of the system was achieved; the time spent on quantification tasks of plates with a high number of colonies might be reduced to a half and occasionally to a third.
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spelling pubmed-93120042022-07-26 Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting Rodrigues, Pedro Miguel Luís, Jorge Tavaria, Freni Kekhasharú Bioengineering (Basel) Article Background: Accurate quantitative analysis of microorganisms is recognized as an essential tool for gauging safety and quality in microbiology settings in a wide range of fields. The enumeration process of viable microorganisms via traditional culturing techniques are methodically convenient and cost-effective, conferring high applicability worldwide. However, manual counting can be time-consuming, laborious and imprecise. Furthermore, particular cases require an urgent and accurate response for effective processing. Methods: To reduce time limitations and discrepancies, this work introduces an image processing method capable of semi-automatically quantifying the number of colony forming units (CFUs). This rapid enumeration technique enables the technician to provide an expeditious assessment of the microbial load of a given sample. To test and validate the system, three bacterial species were cultured, and a labeled database was created, with subsequent image acquisition. Results: The system demonstrated acceptable classification measures; the mean values of Accuracy, Recall and F-measure were: (1) 95%, 95% and 0.95 for E. coli; (2) 91%, 91% and 0.90 for P. aeruginosa; and (3) 84%, 86% and 0.85 for S. aureus. Conclusions: Evidence related to the time-saving potential of the system was achieved; the time spent on quantification tasks of plates with a high number of colonies might be reduced to a half and occasionally to a third. MDPI 2022-06-22 /pmc/articles/PMC9312004/ /pubmed/35877322 http://dx.doi.org/10.3390/bioengineering9070271 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rodrigues, Pedro Miguel
Luís, Jorge
Tavaria, Freni Kekhasharú
Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting
title Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting
title_full Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting
title_fullStr Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting
title_full_unstemmed Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting
title_short Image Analysis Semi-Automatic System for Colony-Forming-Unit Counting
title_sort image analysis semi-automatic system for colony-forming-unit counting
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9312004/
https://www.ncbi.nlm.nih.gov/pubmed/35877322
http://dx.doi.org/10.3390/bioengineering9070271
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