Abstract
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.
| Original language | English |
|---|---|
| Article number | 271 |
| Number of pages | 20 |
| Journal | Bioengineering |
| Volume | 9 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2022 |
Keywords
- Colony forming units
- Enumeration
- Image processing
- Petri-plates
Fingerprint
Dive into the research topics of 'Image analysis semi-automatic system for colony-forming-unit counting'. Together they form a unique fingerprint.Datasets
-
Petri dishes digital images dataset of E.coli, S.aureus and P.aeruginosa
Rodrigues, P. M. (Contributor), Luís, J. (Data Curator) & Tavaria, F. (Contributor), Figshare, 21 Jun 2022
DOI: 10.6084/m9.figshare.20109377.v1
Research data
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver