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Taylor JN, Pélissier A, Mochizuki K, Hashimoto K, Kumamoto Y, Harada Y, Fujita K, Bocklitz T, Komatsuzaki T. Correction for Extrinsic Background in Raman Hyperspectral Images. Anal Chem 2023; 95:12298-12305. [PMID: 37561910 PMCID: PMC10448497 DOI: 10.1021/acs.analchem.3c01406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 07/26/2023] [Indexed: 08/12/2023]
Abstract
Raman hyperspectral microscopy is a valuable tool in biological and biomedical imaging. Because Raman scattering is often weak in comparison to other phenomena, prevalent spectral fluctuations and contaminations have brought advancements in analytical and chemometric methods for Raman spectra. These chemometric advances have been key contributors to the applicability of Raman imaging to biological systems. As studies increase in scale, spectral contamination from extrinsic background, intensity from sources such as the optical components that are extrinsic to the sample of interest, has become an emerging issue. Although existing baseline correction schemes often reduce intrinsic background such as autofluorescence originating from the sample of interest, extrinsic background is not explicitly considered, and these methods often fail to reduce its effects. Here, we show that extrinsic background can significantly affect a classification model using Raman images, yielding misleadingly high accuracies in the distinction of benign and malignant samples of follicular thyroid cell lines. To mitigate its effects, we develop extrinsic background correction (EBC) and demonstrate its use in combination with existing methods on Raman hyperspectral images. EBC isolates regions containing the smallest amounts of sample materials that retain extrinsic contributions that are specific to the device or environment. We perform classification both with and without the use of EBC, and we find that EBC retains biological characteristics in the spectra while significantly reducing extrinsic background. As the methodology used in EBC is not specific to Raman spectra, correction of extrinsic effects in other types of hyperspectral and grayscale images is also possible.
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Affiliation(s)
- J. Nicholas Taylor
- Research
Institute for Electronic Science, Hokkaido
University, Kita 20, Nishi 10, Kita-ku, Sapporo 001-0020, Japan
- Advanced
Photonics and Biosensing Open Innovation Laboratory, AIST-Osaka University, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Aurélien Pélissier
- Research
Institute for Electronic Science, Hokkaido
University, Kita 20, Nishi 10, Kita-ku, Sapporo 001-0020, Japan
- IBM
Research Europe, 8803 Rüschlikon, Switzerland
| | - Kentaro Mochizuki
- Department
of Pathology and Cell Regulation, Kyoto
Prefectural University of Medicine, Kajii-cho 465, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Kosuke Hashimoto
- Department
of Pathology and Cell Regulation, Kyoto
Prefectural University of Medicine, Kajii-cho 465, Kamigyo-ku, Kyoto 602-8566, Japan
- Department
of Biomedical Sciences, School of Biological and Environmental Sciences, Kwansei Gakuin University, 1 Gakuen, Uegahara, Sanda, Hyogo 669-1330, Japan
| | - Yasuaki Kumamoto
- Department
of Applied Physics, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
- Institute
for Open and Transdisciplinary Research Initiatives, Osaka University, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Yoshinori Harada
- Department
of Pathology and Cell Regulation, Kyoto
Prefectural University of Medicine, Kajii-cho 465, Kamigyo-ku, Kyoto 602-8566, Japan
| | - Katsumasa Fujita
- Advanced
Photonics and Biosensing Open Innovation Laboratory, AIST-Osaka University, Yamadaoka, Suita, Osaka 565-0871, Japan
- Department
of Applied Physics, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
- Institute
for Open and Transdisciplinary Research Initiatives, Osaka University, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Thomas Bocklitz
- Leibniz
Institute of Photonic Technology (IPHT), 07745 Jena, Germany
- Institute
of Physical Chemistry and Abbe Center of Photonics (IPC), Friedrich Schiller University, D-07443 Jena, Germany
| | - Tamiki Komatsuzaki
- Research
Institute for Electronic Science, Hokkaido
University, Kita 20, Nishi 10, Kita-ku, Sapporo 001-0020, Japan
- Advanced
Photonics and Biosensing Open Innovation Laboratory, AIST-Osaka University, Yamadaoka, Suita, Osaka 565-0871, Japan
- Institute
for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Kita 21 Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0021, Japan
- Graduate
School of Chemical Sciences and Engineering Materials Chemistry and
Energy Course, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-0812, Japan
- The
Institute of Scientific and Industrial Research, Osaka University, Mihogaoka,
Ibaraki, 8-1, Osaka 567-0047, Japan
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Bouzid K, Greener J, Carrara S, Gosselin B. Portable impedance-sensing device for microorganism characterization in the field. Sci Rep 2023; 13:10526. [PMID: 37386229 PMCID: PMC10310846 DOI: 10.1038/s41598-023-37506-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/22/2023] [Indexed: 07/01/2023] Open
Abstract
A variety of biosensors have been proposed to quickly detect and measure the properties of individual microorganisms among heterogeneous populations, but challenges related to cost, portability, stability, sensitivity, and power consumption limit their applicability. This study proposes a portable microfluidic device based on impedance flow-cytometry and electrical impedance spectroscopy that can detect and quantify the size of microparticles larger than 45 µm, such as algae and microplastics. The system is low cost ($300), portable (5 cm [Formula: see text] 5 cm), low-power (1.2 W), and easily fabricated utilizing a 3D-printer and industrial printed circuit board technology. The main novelty we demonstrate is the use of square wave excitation signal for impedance measurements with quadrature phase-sensitive detectors. A linked algorithm removes the errors associated to higher order harmonics. After validating the performance of the device for complex impedance models, we used it to detect and differentiate between polyethylene microbeads of sizes between 63 and 83 µm, and buccal cells between 45 and 70 µm. A precision of 3% is reported for the measured impedance and a minimum size of 45 µm is reported for the particle characterization.
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Affiliation(s)
- Karim Bouzid
- Department of Electrical and Computer Engineering, Laval University, Quebec-City, G1V 0A6, Canada.
| | - Jesse Greener
- Department of Chemistry, Laval University, Quebec-City, G1V 0A6, Canada
| | - Sandro Carrara
- Institute of Electrical and Micro Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Benoit Gosselin
- Department of Electrical and Computer Engineering, Laval University, Quebec-City, G1V 0A6, Canada
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Siu DMD, Lee KCM, Chung BMF, Wong JSJ, Zheng G, Tsia KK. Optofluidic imaging meets deep learning: from merging to emerging. LAB ON A CHIP 2023; 23:1011-1033. [PMID: 36601812 DOI: 10.1039/d2lc00813k] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microscopes now enables imaging over a range of spatial scales (from molecules to organisms) and temporal window (from microseconds to hours). On the other hand, the staggering diversity of DL algorithms has revolutionized image processing and analysis at the scale and complexity that were once inconceivable. Recognizing these exciting but overwhelming developments, we provide a timely review of their latest trends in the context of lab-on-a-chip imaging, or coined optofluidic imaging. More importantly, here we discuss the strengths and caveats of how to adopt, reinvent, and integrate these imaging techniques and DL algorithms in order to tailor different lab-on-a-chip applications. In particular, we highlight three areas where the latest advances in lab-on-a-chip imaging and DL can form unique synergisms: image formation, image analytics and intelligent image-guided autonomous lab-on-a-chip. Despite the on-going challenges, we anticipate that they will represent the next frontiers in lab-on-a-chip imaging that will spearhead new capabilities in advancing analytical chemistry research, accelerating biological discovery, and empowering new intelligent clinical applications.
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Affiliation(s)
- Dickson M D Siu
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Kelvin C M Lee
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Bob M F Chung
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong
| | - Justin S J Wong
- Conzeb Limited, Hong Kong Science Park, Shatin, New Territories, Hong Kong
| | - Guoan Zheng
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, USA
| | - Kevin K Tsia
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong.
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong
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