Laser speckle time-series correlation analysis for bacteria activity detection

Balmages, Ilya; Bliznuks, Dmitrijs; Liepiņš, Jānis; Zolins, Stivens; Lihachev, Alexey

doi:10.1117/12.2541663

Cited by 11 publications

(8 citation statements)

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“…In the previous studies, the authors described sensitive correlation subpixel analysis, which can help detect bacterial activity and its effects within a colony 8 , 12 . The entire field of the experiment (Petri dish) was divided into small sections of N × N pixels.…”

Section: Methodsmentioning

confidence: 99%

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

Balmages

Liepiņš

Auzins

et al. 2023

Sci Rep

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The microbial colony growth is driven by the activity of the cells located on the edges of the colony. However, this process is not visible unless specific staining or cross-sectioning of the colony is done. Speckle imaging technology is a non-invasive method that allows visualization of the zones of increased microbial activity within the colony. In this study, the laser speckle imaging technique was used to record the growth of the microbial colonies. This method was tested on three different microorganisms: Vibrio natriegens, Escherichia coli, and Staphylococcus aureus. The results showed that the speckle analysis system is not only able to record the growth of the microbial colony but also to visualize the microbial growth activity in different parts of the colony. The developed speckle imaging technique visualizes the zone of “the highest microbial activity” migrating from the center to the periphery of the colony. The results confirm the accuracy of the previous models of colony growth and provide algorithms for analysis of microbial activity within the colony.

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Section: Methodsmentioning

confidence: 99%

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

Balmages

Liepiņš

Auzins

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The speckle pattern is measured using a CMOS sensor. The sensor is located so it captures each speckle grain size, corresponding to approximately 2 by 2 pixels ( 32 – 36 ).…”

Section: Methodsmentioning

confidence: 99%

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis

Lee

Lim²,

Kim

et al. 2022

Microbiol Spectr

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This study performed deep learning of multiple laser scattering patterns by the bacteria in urine to predict positive urine culture. Conventional urine analyzers have limited performance in identifying bacteria in urine. This novel method showed a satisfactory accuracy taking only 30 min of analysis without conventional urine culture. It was also developed to predict the Gram staining reaction of the bacteria. It can be used as a standalone screening tool for urinary tract infection.

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“…In the previous studies, the authors described sensitive correlation subpixel analysis, which can help detect bacterial activity and its effects within a colony 8,12 . The entire field of the experiment (Petri dish) was divided into small sections of NxN pixels.…”

Section: Algorithm Of the Speckle Image Conversion Into Time Signalsmentioning

confidence: 99%

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

Balmages

Liepiņš

Auzins

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The microbial colony growth is driven by the activity of the cells located on the edges of the colony. However, this process is not visible unless specific staining or cross-sectioning of the colony is done. Speckle imaging technology is a non-invasive method that allows visualization of the zones of increased microbial activity within the colony. In this study, the laser speckle imaging technique was used to record the growth of the microbial colony. This method was tested on three different microorganisms: Vibrio natriegens, Escherichia coli, and Staphylococcus aureus. The results showed that the speckle analysis system is not only able to record the growth of the microbial colony but also to visualize the microbial growth activity in different parts of the colony. The developed speckle imaging technique visualizes the zone of “the highest microbial activity” migrating from the center to the periphery of the colony. The results confirm the accuracy of the previous models of colony growth and provide algorithms for analysis of microbial activity within the colony.

show abstract

Laser speckle time-series correlation analysis for bacteria activity detection

Cited by 11 publications

References 0 publications

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

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