Publication
Distinction of different colony types by a smart-data-driven tool
dc.contributor.author | Rodrigues, Pedro Miguel | |
dc.contributor.author | Ribeiro, Pedro | |
dc.contributor.author | Tavaria, Freni Kekhasharú | |
dc.date.accessioned | 2023-01-05T11:11:08Z | |
dc.date.available | 2023-01-05T11:11:08Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Background: Colony morphology (size, color, edge, elevation, and texture), as observed on culture media, can be used to visually discriminate different microorganisms. Methods: This work introduces a hybrid method that combines standard pre-trained CNN keras models and classical machine-learning models for supporting colonies discrimination, developed in Petri-plates. In order to test and validate the system, images of three bacterial species (Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus) cultured in Petri plates were used. Results: The system demonstrated the following Accuracy discrimination rates between pairs of study groups: 92% for Pseudomonas aeruginosa vs. Staphylococcus aureus, 91% for Escherichia coli vs. Staphylococcus aureus and 84% Escherichia coli vs. Pseudomonas aeruginosa. Conclusions: These results show that combining deep-learning models with classical machine-learning models can help to discriminate bacteria colonies with good accuracy ratios. | pt_PT |
dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.doi | 10.3390/bioengineering10010026 | pt_PT |
dc.identifier.eid | 85146835362 | |
dc.identifier.issn | 2306-5354 | |
dc.identifier.pmid | 36671597 | |
dc.identifier.uri | http://hdl.handle.net/10400.14/39741 | |
dc.identifier.wos | 000916494300001 | |
dc.language.iso | eng | pt_PT |
dc.peerreviewed | yes | pt_PT |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Petri-plates | pt_PT |
dc.subject | Colonies | pt_PT |
dc.subject | Machine-learning models | pt_PT |
dc.subject | Discrimination | pt_PT |
dc.title | Distinction of different colony types by a smart-data-driven tool | pt_PT |
dc.type | journal article | |
dspace.entity.type | Publication | |
oaire.citation.issue | 1 | pt_PT |
oaire.citation.title | Bioengineering | pt_PT |
oaire.citation.volume | 10 | pt_PT |
rcaap.rights | openAccess | pt_PT |
rcaap.type | article | pt_PT |