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Accurate estimation of the inhibition zone of antibiotics based on laser speckle imaging and multiple random speckle illuminationoa mark
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Publication Year
2024-05-01
Publisher
Elsevier Ltd
Citation
Computers in Biology and Medicine, Vol.174
Keyword
AntibioticsDiffusion disk methodLaser speckle imagingRandom speckleZone of inhibition
Mesh Keyword
Accurate estimationAntimicrobial susceptibilityBacterial infectionsBacterials activitiesDiffusion disk methodInhibition zonesLaser-speckle imagingRandom speckleSusceptibility testsZone of inhibitionsAlgorithmsAnti-Bacterial AgentsHumansImage Processing, Computer-AssistedLasersMicrobial Sensitivity Tests
All Science Classification Codes (ASJC)
Health InformaticsComputer Science Applications
Abstract
The antimicrobial susceptibility test (AST) plays a crucial role in selecting appropriate antibiotics for the treatment of bacterial infections in patients. The diffusion disk method is widely adopted AST method due to its simplicity, cost-effectiveness, and flexibility. It assesses antibiotic efficacy by measuring the size of the inhibition zone where bacterial growth is suppressed. Quantification of the zone diameter is typically achieved using tools such as rulers, calipers, or automated zone readers, as the inhibition zone is visually discernible. However, challenges arise due to inaccuracies stemming from human errors or image processing of intensity-based images. Here, we proposed a bacterial activity-based AST using laser speckle imaging (LSI) with multiple speckle illumination. LSI measures a speckle pattern produced by interferences of scattered light from the sample; therefore, LSI enables the detection of variation or movement within the sample such as bacterial activity. We found that LSI with multiple speckle illuminations provides consistent and uniform analysis of measured time-varying speckle images. Furthermore, our proposed method effectively identified the boundary of the inhibition zone using the k-means clustering algorithm, exploiting a result of speckle pattern analysis as features. Collectively, the proposed method offers a versatile analytical tool in the diffusion disk method.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34111
DOI
https://doi.org/10.1016/j.compbiomed.2024.108417
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Type
Article
Funding
This research was supported by Ajou University and the National Research Foundation (NRF) of Korea (no. 2021R1C1C1011047 , 2021R1A6A1A10044950 ). This research was also supported by Learning & Academic research institution for Master's\\u00B7PhD students, and Postdocs(LAMP) Program of the National Research Foundation of Korea(NRF) grant funded by the Ministry of Education (No. RS-2023-00285390 ).
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Yoon, Jonghee 윤종희
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