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Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning

In this study, we propose a technique for identifying and imaging reagents through shielding over a wide dynamic range using a real-time terahertz (THz) spectroscopy system with multi-wavelength THz parametric generation/detection and machine learning. To quickly identify reagents through shielding,...

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Autores principales: Murate, Kosuke, Mine, Sota, Torii, Yuki, Inoue, Hyuga, Kawase, Kodo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406837/
https://www.ncbi.nlm.nih.gov/pubmed/37550379
http://dx.doi.org/10.1038/s41598-023-40013-y
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author Murate, Kosuke
Mine, Sota
Torii, Yuki
Inoue, Hyuga
Kawase, Kodo
author_facet Murate, Kosuke
Mine, Sota
Torii, Yuki
Inoue, Hyuga
Kawase, Kodo
author_sort Murate, Kosuke
collection PubMed
description In this study, we propose a technique for identifying and imaging reagents through shielding over a wide dynamic range using a real-time terahertz (THz) spectroscopy system with multi-wavelength THz parametric generation/detection and machine learning. To quickly identify reagents through shielding, the spectral information of the “detection Stokes beam” is used for reagent recognition via machine learning. In general THz wave-based reagent identification, continuous spectra are acquired and analyzed quantitatively by post-processing. In actual applications, however, such as testing for illicit drugs in mail, the technology must be able to quickly identify reagents as opposed to quantifying the amount present. In multi-wavelength THz parametric generation/detection, THz spectral information can be measured instantly using a “multi-wavelength detection Stokes beam” and near-infrared (NIR) camera. Moreover, machine learning enables reagent identification in real-time and over a wide dynamic range. Furthermore, by plotting the identification results as pixel values, the spatial distribution of reagents can be imaged at high speed without the need for post-processing.
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spelling pubmed-104068372023-08-09 Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning Murate, Kosuke Mine, Sota Torii, Yuki Inoue, Hyuga Kawase, Kodo Sci Rep Article In this study, we propose a technique for identifying and imaging reagents through shielding over a wide dynamic range using a real-time terahertz (THz) spectroscopy system with multi-wavelength THz parametric generation/detection and machine learning. To quickly identify reagents through shielding, the spectral information of the “detection Stokes beam” is used for reagent recognition via machine learning. In general THz wave-based reagent identification, continuous spectra are acquired and analyzed quantitatively by post-processing. In actual applications, however, such as testing for illicit drugs in mail, the technology must be able to quickly identify reagents as opposed to quantifying the amount present. In multi-wavelength THz parametric generation/detection, THz spectral information can be measured instantly using a “multi-wavelength detection Stokes beam” and near-infrared (NIR) camera. Moreover, machine learning enables reagent identification in real-time and over a wide dynamic range. Furthermore, by plotting the identification results as pixel values, the spatial distribution of reagents can be imaged at high speed without the need for post-processing. Nature Publishing Group UK 2023-08-07 /pmc/articles/PMC10406837/ /pubmed/37550379 http://dx.doi.org/10.1038/s41598-023-40013-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Murate, Kosuke
Mine, Sota
Torii, Yuki
Inoue, Hyuga
Kawase, Kodo
Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
title Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
title_full Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
title_fullStr Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
title_full_unstemmed Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
title_short Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
title_sort wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406837/
https://www.ncbi.nlm.nih.gov/pubmed/37550379
http://dx.doi.org/10.1038/s41598-023-40013-y
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