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...

Descrición completa

Gardado en:
Detalles Bibliográficos
Main Authors: Qing He, Wen Yang, Weiquan Luo, Stefan Wilhelm, Binbin Weng
Formato: Artigo
Idioma:Inglês
Publicado: MDPI AG 2022-04-01
Series:Biosensors
Assuntos:
Raman spectroscopy
PCA
machine learning
non-invasive imaging
fast Raman imaging
cancer cells
Acceso en liña:https://www.mdpi.com/2079-6374/12/4/250
Tags: Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!

Títulos similares