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Article

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging

by 1,*,†,‡, 2,†, 3,§, 2 and 1,*
1
School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73072, USA
2
Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73072, USA
3
Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50010, USA
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Current address: Mechanical Engineering, Tufts University, Medford, MA 02155, USA.
§
Current address: Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Biosensors 2022, 12(4), 250; https://doi.org/10.3390/bios12040250
Received: 16 March 2022 / Revised: 10 April 2022 / Accepted: 12 April 2022 / Published: 15 April 2022
This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quick Raman spectroscopic imaging, a hyperspectral data processing approach based on machine learning methods proved capable of presenting the cell structure and distinguishing cancer cells from non-cancer muscle cells without compromising full-spectrum information. This study discovered that biomolecular information–nucleic acids, proteins, and lipids—from cells could be retrieved efficiently from low-quality hyperspectral Raman datasets and then employed for cell line differentiation. View Full-Text
Keywords: Raman spectroscopy; PCA; machine learning; non-invasive imaging; fast Raman imaging; cancer cells Raman spectroscopy; PCA; machine learning; non-invasive imaging; fast Raman imaging; cancer cells
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MDPI and ACS Style

He, Q.; Yang, W.; Luo, W.; Wilhelm, S.; Weng, B. Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging. Biosensors 2022, 12, 250. https://doi.org/10.3390/bios12040250

AMA Style

He Q, Yang W, Luo W, Wilhelm S, Weng B. Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging. Biosensors. 2022; 12(4):250. https://doi.org/10.3390/bios12040250

Chicago/Turabian Style

He, Qing, Wen Yang, Weiquan Luo, Stefan Wilhelm, and Binbin Weng. 2022. "Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging" Biosensors 12, no. 4: 250. https://doi.org/10.3390/bios12040250

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