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 language | English |
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Article number | 1279667 |
Pages (from-to) | 01-10 |
Number of pages | 10 |
Journal | Frontiers in Microbiology |
Volume | 14 |
DOIs | |
Publication status | Published - 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