SERS nanoparticles are powerful optical contrast agents for imaging assays. Their highly specific sets of narrow spectral bands make them well suited for multiplexing applications, and their enhanced inelastic scattering cross sections enable rapid, high content imaging. Multiplexed hyperspectral imaging datasets commonly undergo a spectral unmixing postprocessing step using a compensation matrix of reference spectra to produce quantitative image channels. We perform hyperspectral Raman imaging on mixtures with increasing plexity and varying degrees of linear system conditioning and compare against the ground truth to determine the most robust workflow for quantitative biological SERS imaging.
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