Affiliations: [a] Instituto Politécnico Nacional-UPIIG, Mineral de Valenciana N. 200, Industrial Puerto Interior, Silao de la Victoria, GTO, México | [b] Departamento de Ingeniería Física – DCI, Universidad de Guanajuato campus León, Loma del Bosque, Lomas del Campestre, León, GTO, México | [c] Departamento de Ingeniería Eléctrica – DICIS, Universidad de Guanajuato campus Irapuato-Salamanca km 3.5 Carretera Salamanca-Valle de Santiago + 1.8 Comunidad de Pablo Blanco, GTO, México
Correspondence:
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Corresponding author. Rafael Guzmán-Cabrera, DICIS, Universidad de Guanajuato campus Irapuato-Salamanca km 3.5 Carretera Salamanca-Valle de Santiago+1.8 Comunidad de Pablo Blanco, GTO, México. E-mail: [email protected].
Abstract: In this work, we propose a practical approach to access and visualize relevant information on the spatial distribution on the anything sample about its biochemical composition. In order to carry out this analysis, we use a Raman spectroscopy technique to obtain spectral maps with specific spatial resolution (1 and 5 micrometers) over a selected region of the sample. Our study relies on the application of a Principal Component Analysis on the cross-correlations between the spectral blocks measured, within a certain spectral window of interest. The associated values of these principal components are used to build low-resolution images (with the same spatial resolution of the Raman scan) in which the relevant information on the chemical composition is already encoded. Finally, the spatial resolution of the principal components images was numerically enhanced in the post-processing through standard linear interpolation algorithms. In this way, we can map and visualize, simultaneously, the spatial and spectral information. The results suggest that the Raman spectroscopy imaging is a powerful tool for determining the biochemistry of organic and inorganic samples based on spectral scanning and thus determine compounds concentrations of medical interest. The proposed methodology is rather general and it could be extended to other spectroscopic measurement techniques where the spatial mapping of the spectral information is needed.
Keywords: Raman spectroscopy, principal components analysis, spectral maps, image reconstruction
