This study aims to extract layer-resolved fluorescence efficiency and emission spectral shape of in-vivo cervical mucosa tissue by a two-layered fluorescence Monte Carlo model. The emission spectra are modeled to have skew-normal distributions, and genetic algorithm is used to find parameters that optimize the fit to the measured spectra. Excellent model fits suggest that the proposed method provide more accurate evaluation of intrinsic fluorescence properties of the cervical mucosa, which has the potential to aid the non-invasive diagnosis of cervical precancers.

© 2018 The Author(s)

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