Quantitative chemical imaging and unsupervised analysis using hyperspectral coherent anti-Stokes Raman scattering microscopy.

ABSTRACT: In this work, we report a method to acquire and analyze hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy images of organic materials and biological samples resulting in an unbiased quantitative chemical analysis. The method employs singular value decomposition on the square root of the CARS intensity, providing an automatic determination of the components above noise, which are retained. Complex CARS susceptibility spectra, which are linear in the chemical composition, are retrieved from the CARS intensity spectra using the causality of the susceptibility by two methods, and their performance is evaluated by comparison with Raman spectra. We use non-negative matrix factorization applied to the imaginary part and the nonresonant real part of the susceptibility with an a

SUBMITTER: Masia F 

PROVIDER: S-EPMC3889493 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature