Hyperspectral stimulated Raman scattering (hSRS) is a label-free microspectroscopic modality that enables live-cell metabolic imaging with chemical specificity. Yet, hSRS in the CH region has low throughput and poor chemical specificity, which limits its application to a broader range of metabolic studies. We propose a high-content, high-throughput hSRS imaging method by a sparsity-driven spectral unmixing and active spectral sub-sampling. We unprecedently generate chemical maps of four major metabolic species (lipid, protein, nucleic acid and carbohydrate) in a Mia PaCa-2 cell using seven spectral frames in the CH region, improving the acquisition speed by over an order of magnitude.
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