Bacteria identification in an optical system with optimized diffraction pattern registration condition supported by enhanced statistical analysis

Suchwałko, Agnieszka; Buzalewicz, Igor; Podbielska, Halina

doi:10.1364/oe.22.026312

Cited by 16 publications

(16 citation statements)

References 8 publications

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“…However, for some bacterial species or strains, unique diffraction patterns can only be detected at a specific distance. Therefore, time-consuming measurements of the diffraction/scattering patterns in different locations of the registration plane are required [ 17 ]. In contrast, with PSDIH it is possible to record one digital hologram, and numerically reconstruct the amplitude distribution in all desired observation planes.…”

Section: Resultsmentioning

confidence: 99%

“…The special image processing algorithms and features extraction developed in our group, were exploited for the statistical analysis of the recorded optical signatures of bacterial colonies [ 12 , 15 – 17 ]. The recorded holograms, reconstructed phase and amplitude patterns, as well as the reconstructed diffraction intensity patterns of bacterial colonies were examined.…”

Section: Methodsmentioning

confidence: 99%

“…The experiments performed using our system with converging spherical wave illumination have shown that the Fresnel diffraction patterns of colonies were unique and allowed for species discrimination [ 12 – 16 ]. The proposed statistical analysis algorithm for Fresnel diffraction pattern analysis enables identification with nearly 99% accuracy [ 17 ]. Moreover, experiments performed by other researchers on four different strains of Escherichia coli , also demonstrated that it is possible to identify bacterial strains with a 82% recognition rate [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

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Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography

Buzalewicz¹,

Kujawińska²,

Krauze³

et al. 2016

PLoS ONE

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The use of light diffraction for the microbiological diagnosis of bacterial colonies was a significant breakthrough with widespread implications for the food industry and clinical practice. We previously confirmed that optical sensors for bacterial colony light diffraction can be used for bacterial identification. This paper is focused on the novel perspectives of this method based on digital in-line holography (DIH), which is able to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the bacterial colony in any chosen observation plane behind the object from single digital hologram. Analysis of the amplitude and phase patterns inside a colony revealed its unique optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, on a computational level, it is possible to select the desired scattered/diffracted pattern within the entire observation volume that exhibits the largest amount of unique, differentiating bacterial features. These properties distinguish this method from the already proposed sensing techniques based on light diffraction/scattering of bacterial colonies. The reconstructed diffraction patterns have a similar spatial distribution as the recorded Fresnel patterns, previously applied for bacterial identification with over 98% accuracy, but they are characterized by both intensity and phase distributions. Our results using digital holography provide new optical discriminators of bacterial species revealed in one single step in form of new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, as well as diffraction patterns from all observation space, which exhibit species-dependent features. To the best of our knowledge, this is the first report on bacterial colony analysis via digital holography and our study represents an innovative approach to the subject.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography

Buzalewicz¹,

Kujawińska²,

Krauze³

et al. 2016

PLoS ONE

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“…First, speckles are sensitive to both amplitude and phase changes induced by bacteria. Since bacterial colonies have been reported to exert phase modulation 46 , speckle patterns can sensitively respond to changes of optical path length in bacterial samples better than amplitude-dependent detection such as camera-vision based AST (~ 3.5 h) 47 .…”

Section: Discussionmentioning

confidence: 99%

Rapid antimicrobial susceptibility test using spatiotemporal analysis of laser speckle dynamics of bacterial colonies

Han

Baek

et al. 2019

Preprint

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Antimicrobial susceptibility testing (AST) is crucial for providing appropriate choices and doses of antibiotics to patients.However, standard ASTs require a time-consuming incubation of about 16-20 h for visual accumulation of bacteria, limiting the use of AST for an early prescription. In this study, we propose a rapid AST based on laser speckle formation (LSF) that enables rapid detection of bacterial growth, with the same sample preparation protocol as in solid-based ASTs.The proposed method exploits the phenomenon that well-grown bacterial colonies serve as optical diffusers, which convert a plane-wave laser beam into speckles. The generation of speckle patterns indicates bacterial growth at given antibiotic concentrations. Speckle formation is evaluated by calculating the spatial autocorrelation of speckle images, and bacterial growth is determined by tracking the autocorrelation value over time. We demonstrated the performance of the proposed method for several combinations of bacterial species and antibiotics to achieve the AST in 2-4.5 hours.Furthermore, we also demonstrated the sensitivity of the technique for low bacterial density. The proposed method can be a powerful tool for rapid, simple, and low-cost AST.

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“…of bacterial identification[47] [48]. For this purpose, an optical system with convergingspherical wave illumination of colonies for Fresnel patterns recording as digital images was devised.…”

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confidence: 99%

Image Analysis in Microbiology: A Review

Pushchino¹

2016

JCC

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This review is focused on using computer image analysis as a means of objective and quantitative characterizing optical images of the macroscopic (e.g. microbial colonies) and the microscopic (e.g. single cell) objects in the microbiological research. This is the way of making many visual inspection assays more objective and less time and labor consuming. Also, it can provide new visually inaccessible information on relation between some optical parameters and various biological features of the microbial cultures. Of special interest is application of image analysis in fluorescence microscopy as it opens new ways of using fluorescence based methodology for single microbial cell studies. Examples of using image analysis in the studies of both the macroscopic and the microscopic microbiological objects obtained by various imaging techniques are presented and discussed.

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Bacteria identification in an optical system with optimized diffraction pattern registration condition supported by enhanced statistical analysis

Cited by 16 publications

References 8 publications

Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography

Novel Perspectives on the Characterization of Species-Dependent Optical Signatures of Bacterial Colonies by Digital Holography

Rapid antimicrobial susceptibility test using spatiotemporal analysis of laser speckle dynamics of bacterial colonies

Image Analysis in Microbiology: A Review

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