We discuss the implementation of wavelength-swept coherent Raman scattering (CRS) microscopy for the rapid acquisition of hyperspectral datacubes. We highlight two multivariate analysis approaches for efficiently generating spectroscopic maps from the acquired data: principal component analysis (PCA), which is a popular method for extracting information from multidimensional datasets, and vertex component analysis (VCA), which has previously been successfully used for the analysis of spontaneous Raman microscopy data. Through several biomedical imaging examples, we discuss the advantages and disadvantages of these approaches for CRS microscopy.
Eric O. Potma and Alba Alfonso Garcia, "Mapping biological tissues with hyperspectral coherent Raman scattering microscopy
(Conference Presentation)," Proc. SPIE 9720, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management, 97200F (Presented at SPIE BiOS: February 13, 2016; Published: 28 June 2016); https://doi.org/10.1117/12.2213565.4848767886001.
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