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Article ; Online: Accurate estimation of the inhibition zone of antibiotics based on laser speckle imaging and multiple random speckle illumination.

Kim, Donghyeok / Lee, Jongseo / Yoon, Jonghee

2024 Volume 174, Page(s) 108417

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, ...

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.
MeSH term(s)	Anti-Bacterial Agents/pharmacology ; Microbial Sensitivity Tests ; Humans ; Image Processing, Computer-Assisted/methods ; Algorithms ; Lasers
Chemical Substances	Anti-Bacterial Agents
Language	English
Publishing date	2024-04-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	127557-4
ISSN	1879-0534 ; 0010-4825
ISSN (online)	1879-0534
ISSN	0010-4825
DOI	10.1016/j.compbiomed.2024.108417
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Assessment of angle-dependent spectral distortion to develop accurate hyperspectral endoscopy.

Lee, Jungwoo / Yoon, Jonghee

Scientific reports

2022 Volume 12, Issue 1, Page(s) 11892

Abstract: Hyperspectral endoscopy has shown its potential to improve disease diagnosis in gastrointestinal tracts. Recent approaches in developing hyperspectral endoscopy are mainly focusing on enhancing image speed and quality of spectral information under a ... ...

Abstract	Hyperspectral endoscopy has shown its potential to improve disease diagnosis in gastrointestinal tracts. Recent approaches in developing hyperspectral endoscopy are mainly focusing on enhancing image speed and quality of spectral information under a clinical environment, but there are many issues in obtaining consistent spectral information due to complicated imaging conditions, including imaging angle, non-uniform illumination, working distance, and low reflected signal. We quantitatively investigated the effect of imaging angle on the distortion of spectral information by exploiting a bifurcated fiber, spectrometer, and tissue-mimicking phantom. Spectral distortion becomes severe as increasing the angle of the imaging fiber or shortening camera exposure time for fast image acquisition. Moreover, spectral ranges from 450 to 550 nm are more susceptible to the angle-dependent spectral distortion than longer spectral ranges. Therefore, imaging angles close to normal and longer target spectral ranges with enough detector exposure time could minimize spectral distortion in hyperspectral endoscopy. These findings will help implement clinical HSI endoscopy for the robust and accurate measurement of spectral information from patients in vivo.
MeSH term(s)	Diagnostic Imaging/methods ; Endoscopy ; Humans ; Lighting ; Phantoms, Imaging
Language	English
Publishing date	2022-07-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-16232-0
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Article ; Online: Extended Axion Dark Matter Search Using the CAPP18T Haloscope.

Yang, Byeongsu / Yoon, Hojin / Ahn, Moohyun / Lee, Youngjae / Yoo, Jonghee

Physical review letters

2023 Volume 131, Issue 8, Page(s) 81801

Abstract: We report an extended search for the axion dark matter using the CAPP18T haloscope. The CAPP18T experiment adopts innovative technologies of a high-temperature superconducting magnet and a Josephson parametric converter. The CAPP18T detector was ... ...

Abstract	We report an extended search for the axion dark matter using the CAPP18T haloscope. The CAPP18T experiment adopts innovative technologies of a high-temperature superconducting magnet and a Josephson parametric converter. The CAPP18T detector was reconstructed after an unexpected incident of the high-temperature superconducting magnet quenching. The system reconstruction includes rebuilding the magnet, improving the impedance matching in the microwave chain, and mechanically readjusting the tuning rod to the cavity for improved thermal contact. The total system noise temperature is ∼0.6 K. The coupling between the cavity and the strong antenna is maintained at β≃2 to enhance the axion search scanning speed. The scan frequency range is from 4.8077 to 4.8181 GHz. No significant indication of the axion dark matter signature is observed. The results set the best upper bound of the axion-photon-photon coupling (g_{aγγ}) in the mass ranges of 19.883 to 19.926 μeV at ∼0.7×\|g_{aγγ}^{KSVZ}\| or ∼1.9×\|g_{aγγ}^{DFSZ}\| with 90% confidence level. The results demonstrate that a reliable search of the high-mass dark matter axions can be achieved beyond the benchmark models using the technology adopted in CAPP18T.
Language	English
Publishing date	2023-09-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.131.081801
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Article ; Online: Targeted multispectral filter array design for the optimization of endoscopic cancer detection in the gastrointestinal tract.

Taylor-Williams, Michaela / Tao, Ran / Sawyer, Travis W / Waterhouse, Dale J / Yoon, Jonghee / Bohndiek, Sarah E

Journal of biomedical optics

2024 Volume 29, Issue 3, Page(s) 36005

Abstract: Significance: Color differences between healthy and diseased tissue in the gastrointestinal (GI) tract are detected visually by clinicians during white light endoscopy; however, the earliest signs of cancer are often just a slightly different shade of ... ...

Abstract	Significance: Color differences between healthy and diseased tissue in the gastrointestinal (GI) tract are detected visually by clinicians during white light endoscopy; however, the earliest signs of cancer are often just a slightly different shade of pink compared to healthy tissue making it hard to detect. Improving contrast in endoscopy is important for early detection of disease in the GI tract during routine screening and surveillance. Aim: We aim to target alternative colors for imaging to improve contrast using custom multispectral filter arrays (MSFAs) that could be deployed in an endoscopic "chip-on-tip" configuration. Approach: Using an open-source toolbox, Opti-MSFA, we examined the optimal design of MSFAs for early cancer detection in the GI tract. The toolbox was first extended to use additional classification models ( Results: We examined the variation of the spectral and spatial classification accuracies as a function of the number of bands. The MSFA configurations tested showed good classification accuracies when compared to the full hyperspectral data available from the clinical spectra used in these studies. Conclusion: The ability to retain good classification accuracies with a reduced number of spectral bands could enable the future deployment of multispectral imaging in an endoscopic chip-on-tip configuration using simplified MSFA hardware. Further studies using an expanded clinical dataset are needed to confirm these findings.
MeSH term(s)	Humans ; Endoscopy, Gastrointestinal ; Diagnostic Imaging ; Neoplasms ; Esophagus
Language	English
Publishing date	2024-03-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	1309154-2
ISSN	1560-2281 ; 1083-3668
ISSN (online)	1560-2281
ISSN	1083-3668
DOI	10.1117/1.JBO.29.3.036005
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Quenching of a no-insulation high-temperature superconducting magnet.

Ahn, Moohyun / Yang, Byeongsu / Lee, Youngjae / Yoon, Hojin / Park, Heejun / Kim, DongLak / Yoo, Jonghee

The Review of scientific instruments

2023 Volume 94, Issue 8

Abstract: We report details on the quenching incident of an 18 T high-temperature superconducting (HTS) magnet, which occurred in December 2020. It has been received that the no-insulation (NI) design of an HTS magnet is relatively safe in quenching. However, the ... ...

Abstract	We report details on the quenching incident of an 18 T high-temperature superconducting (HTS) magnet, which occurred in December 2020. It has been received that the no-insulation (NI) design of an HTS magnet is relatively safe in quenching. However, the NI design could not completely prevent the magnet from quenching and damaging the associated system. Due to significant vibrations and fast energy dissipation during quenching, the magnet and the detector components are seriously damaged. The manufacturer inspected the magnet after the incident and repaired it in the spring of 2021. The magnet showed stable and consistent performance after the repair. It is evident that the NI-HTS magnet still requires quench protection circuits to secure the magnet and associated system.
Language	English
Publishing date	2023-12-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	209865-9
ISSN	1089-7623 ; 0034-6748
ISSN (online)	1089-7623
ISSN	0034-6748
DOI	10.1063/5.0133172
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Article ; Online: A background correction method to compensate illumination variation in hyperspectral imaging.

Jonghee Yoon / Alexandru Grigoroiu / Sarah E Bohndiek

PLoS ONE, Vol 15, Iss 3, p e

2020 Volume 0229502

Abstract: Hyperspectral imaging (HSI) can measure both spatial (morphological) and spectral (biochemical) information from biological tissues. While HSI appears promising for biomedical applications, interpretation of hyperspectral images can be challenging when ... ...

Abstract	Hyperspectral imaging (HSI) can measure both spatial (morphological) and spectral (biochemical) information from biological tissues. While HSI appears promising for biomedical applications, interpretation of hyperspectral images can be challenging when data is acquired in complex biological environments. Variations in surface topology or optical power distribution at the sample, encountered for example during endoscopy, can lead to errors in post-processing of the HSI data, compromising disease diagnostic capabilities. Here, we propose a background correction method to compensate for such variations, which estimates the optical properties of illumination at the target based on the normalised spectral profile of the light source and the measured HSI intensity values at a fixed wavelength where the absorption characteristics of the sample are relatively low (in this case, 800 nm). We demonstrate the feasibility of the proposed method by imaging blood samples, tissue-mimicking phantoms, and ex vivo chicken tissue. Moreover, using synthetic HSI data composed from experimentally measured spectra, we show the proposed method would improve statistical analysis of HSI data. The proposed method could help the implementation of HSI techniques in practical clinical applications, where controlling the illumination pattern and power is difficult.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Deep learning applied to hyperspectral endoscopy for online spectral classification

Alexandru Grigoroiu / Jonghee Yoon / Sarah E. Bohndiek

Scientific Reports, Vol 10, Iss 1, Pp 1-

2020 Volume 10

Abstract: Abstract Hyperspectral imaging (HSI) is being explored in endoscopy as a tool to extract biochemical information that may improve contrast for early cancer detection in the gastrointestinal tract. Motion artefacts during medical endoscopy have ... ...

Abstract	Abstract Hyperspectral imaging (HSI) is being explored in endoscopy as a tool to extract biochemical information that may improve contrast for early cancer detection in the gastrointestinal tract. Motion artefacts during medical endoscopy have traditionally limited HSI application, however, recent developments in the field have led to real-time HSI deployments. Unfortunately, traditional HSI analysis methods remain unable to rapidly process the volume of hyperspectral data in order to provide real-time feedback to the operator. Here, a convolutional neural network (CNN) is proposed to enable online classification of data obtained during HSI endoscopy. A five-layered CNN was trained and fine-tuned on a dataset of 300 hyperspectral endoscopy images acquired from a planar Macbeth ColorChecker chart and was able to distinguish between its 18 constituent colors with an average accuracy of 94.3% achieved at 8.8 fps. Performance was then tested on a set of images simulating an endoscopy environment, consisting of color charts warped inside a rigid tube mimicking a lumen. The algorithm proved robust to such variations, with classification accuracies over 90% being obtained despite the variations, with an average drop in accuracy of 2.4% being registered at the points of longest working distance and most inclination. For further validation of the color-based classification system, ex vivo videos of a methylene blue dyed pig esophagus and images of different disease stages in the human esophagus were analyzed, showing spatially distinct color classifications. These results suggest that the CNN has potential to provide color-based classification during real-time HSI in endoscopy.
Keywords	Medicine ; R ; Science ; Q
Subject code	571
Language	English
Publishing date	2020-03-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A background correction method to compensate illumination variation in hyperspectral imaging.

Yoon, Jonghee / Grigoroiu, Alexandru / Bohndiek, Sarah E

PloS one

2020 Volume 15, Issue 3, Page(s) e0229502

Abstract	Hyperspectral imaging (HSI) can measure both spatial (morphological) and spectral (biochemical) information from biological tissues. While HSI appears promising for biomedical applications, interpretation of hyperspectral images can be challenging when data is acquired in complex biological environments. Variations in surface topology or optical power distribution at the sample, encountered for example during endoscopy, can lead to errors in post-processing of the HSI data, compromising disease diagnostic capabilities. Here, we propose a background correction method to compensate for such variations, which estimates the optical properties of illumination at the target based on the normalised spectral profile of the light source and the measured HSI intensity values at a fixed wavelength where the absorption characteristics of the sample are relatively low (in this case, 800 nm). We demonstrate the feasibility of the proposed method by imaging blood samples, tissue-mimicking phantoms, and ex vivo chicken tissue. Moreover, using synthetic HSI data composed from experimentally measured spectra, we show the proposed method would improve statistical analysis of HSI data. The proposed method could help the implementation of HSI techniques in practical clinical applications, where controlling the illumination pattern and power is difficult.
MeSH term(s)	Algorithms ; Animals ; Chickens ; Fluorescent Dyes ; Lighting/instrumentation ; Machine Learning ; Mice ; Optical Imaging/methods ; Phantoms, Imaging
Chemical Substances	Fluorescent Dyes
Language	English
Publishing date	2020-03-13
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0229502
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Deep learning applied to hyperspectral endoscopy for online spectral classification.

Grigoroiu, Alexandru / Yoon, Jonghee / Bohndiek, Sarah E

Scientific reports

2020 Volume 10, Issue 1, Page(s) 3947

Abstract: Hyperspectral imaging (HSI) is being explored in endoscopy as a tool to extract biochemical information that may improve contrast for early cancer detection in the gastrointestinal tract. Motion artefacts during medical endoscopy have traditionally ... ...

Abstract	Hyperspectral imaging (HSI) is being explored in endoscopy as a tool to extract biochemical information that may improve contrast for early cancer detection in the gastrointestinal tract. Motion artefacts during medical endoscopy have traditionally limited HSI application, however, recent developments in the field have led to real-time HSI deployments. Unfortunately, traditional HSI analysis methods remain unable to rapidly process the volume of hyperspectral data in order to provide real-time feedback to the operator. Here, a convolutional neural network (CNN) is proposed to enable online classification of data obtained during HSI endoscopy. A five-layered CNN was trained and fine-tuned on a dataset of 300 hyperspectral endoscopy images acquired from a planar Macbeth ColorChecker chart and was able to distinguish between its 18 constituent colors with an average accuracy of 94.3% achieved at 8.8 fps. Performance was then tested on a set of images simulating an endoscopy environment, consisting of color charts warped inside a rigid tube mimicking a lumen. The algorithm proved robust to such variations, with classification accuracies over 90% being obtained despite the variations, with an average drop in accuracy of 2.4% being registered at the points of longest working distance and most inclination. For further validation of the color-based classification system, ex vivo videos of a methylene blue dyed pig esophagus and images of different disease stages in the human esophagus were analyzed, showing spatially distinct color classifications. These results suggest that the CNN has potential to provide color-based classification during real-time HSI in endoscopy.
Language	English
Publishing date	2020-03-03
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-60574-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Searching for Invisible Axion Dark Matter with an 18 T Magnet Haloscope.

Lee, Youngjae / Yang, Byeongsu / Yoon, Hojin / Ahn, Moohyun / Park, Heejun / Min, Byeonghun / Kim, DongLak / Yoo, Jonghee

Physical review letters

2022 Volume 128, Issue 24, Page(s) 241805

Abstract: We report the first search results for axion dark matter using an 18 T high-temperature superconducting magnet haloscope. The scan frequency ranges from 4.7789 to 4.8094 GHz. No significant signal consistent with the Galactic halo dark matter axion is ... ...

Abstract	We report the first search results for axion dark matter using an 18 T high-temperature superconducting magnet haloscope. The scan frequency ranges from 4.7789 to 4.8094 GHz. No significant signal consistent with the Galactic halo dark matter axion is observed. The results set the best upper bound of axion-photon-photon coupling (g_{aγγ}) in the mass ranges of 19.764 to 19.771 μeV (19.863 to 19.890 μeV) at 1.5×\|g_{aγγ}^{KSVZ}\| (1.7×\|g_{aγγ}^{KSVZ}\|), and 19.772 to 19.863 μeV at 2.7×\|g_{aγγ}^{KSVZ}\| with 90% confidence level, respectively. This remarkable sensitivity in the high mass region of dark matter axion is achieved by using the strongest magnetic field among the existing haloscope experiments and realizing a low-noise amplification of microwave signals using a Josephson parametric converter.
Language	English
Publishing date	2022-07-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.128.241805
Database	MEDical Literature Analysis and Retrieval System OnLINE

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