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

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 dat...

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Bibliografiska uppgifter
Huvudupphovsmän: Qing He, Wen Yang, Weiquan Luo, Stefan Wilhelm, Binbin Weng
Materialtyp: Artigo
Språk:Inglês
Publicerad: MDPI AG 2022-04-01
Serie:Biosensors
Ämnen:
Raman spectroscopy
PCA
machine learning
non-invasive imaging
fast Raman imaging
cancer cells
Länkar:https://www.mdpi.com/2079-6374/12/4/250
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