More patients diagnosed with stage I (local) melanoma die than any other metastatic stage, because there exists no biomarker to reliably diagnose metastatic melanoma, preventing many patients to receive appropriate treatment. We pursue an approach based on femtosecond pump-probe microscopy of melanin; a natural pigment found in most melanoma. The measured pump-probe signals of melanin are complex superpositions of multiple nonlinear processes, making interpretation challenging. We demonstrate how polarization control and data fitting are used to decompose melanin signals into their underlying nonlinear interactions. False colored images of a small set of melanoma tumors, based on specific nonlinear interactions, correlate with clinical concern. This approach of decomposing pump-probe signals is applicable to a multitude of different samples.
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