Tools for Classification of Growing/Non-Growing Bacterial Colonies Using Laser Speckle Imaging
Frontiers in Microbiology 2023
Ilya Balmages, Janis Liepins, Stivens Zolins, Dmitrijs Bļizņuks, Renārs Broks, Ilze Lihacova, Alexey Lihachev

Prior research has indicated the feasibility of assessing growth—associated activity in bacterial colonies through the application of laser speckle imaging techniques. A subpixel correlation method was employed to identify variations in sequential laser speckle images, thereby facilitating the visualization of specific zones indicative of microbial growth within the colony. Such differentiation between active (growing) and inactive (non-growing) bacterial colonies holds considerable implications for medical applications, like bacterial response to certain drugs or antibiotics. The present study substantiates the capability of laser speckle imaging to categorize bacterial colonies as growing or non-growing, a parameter which nonvisible in colonies when observed under white light illumination. Copyright © 2023 Balmages, Liepins, Zolins, Bliznuks, Broks, Lihacova and Lihachev.


Keywords
artificial neural network; image processing; laser speckle imaging; microorganism activity estimation; sensitive subpixel correlation method
DOI
10.3389/fmicb.2023.1279667
Hyperlink
https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2023.1279667/full

Balmages, I., Liepins, J., Zolins, S., Bļizņuks, D., Broks, R., Lihacova, I., Lihachev, A. Tools for Classification of Growing/Non-Growing Bacterial Colonies Using Laser Speckle Imaging. Frontiers in Microbiology, 2023, Vol. 14, Article number 1279667. ISSN 1664-302X. Available from: doi:10.3389/fmicb.2023.1279667

Publication language
English (en)
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