Tools for classification of growing/non-growing bacterial colonies using laser speckle imaging

Ilya Balmages (Corresponding Author), Janis Liepins, Stivens Zolins, Dmitrijs Bliznuks, Renars Broks, Ilze Lihacova, Alexey Lihachev

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
16 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article number1279667
Pages (from-to)01-10
Number of pages10
JournalFrontiers in Microbiology
Volume14
DOIs
Publication statusPublished - 20 Oct 2023

Keywords*

  • artificial neural network
  • image processing
  • laser speckle imaging
  • microorganism activity estimation
  • sensitive subpixel correlation method

Field of Science*

  • 1.6 Biological sciences
  • 1.3 Physical sciences

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database

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