Improved estimation of the optical properties in a skin five-layer model from spatially resolved diffuse reflectance spectra using a layer-by-layer approach and optimized combinations of wavelengths and source-detector distances

Spatially resolved diffuse reflectance spectroscopy (SR-DRS) is a widely studied optical biopsy technique to investigate and to diagnose skin tissue modifications due to pathologies such as cancers. One way to exploit clinical spectra acquired with a SR-DRS medical device consists in estimating diagnostically relevant skin optical properties that is, by solving an inverse problem based on numerical simulations to generate spectra in accordance with the technical and geometrical features of the latter device. For realistic multi-layer skin media, the simultaneous estimation of layer-wise optical properties of interest is quite challenging (difficulty of convergence or non-unicity of the solution) and time consuming, especially for one or several parameters to be estimated in more than three layers of a skin model. To tackle this problem, the work presented here proposes an improved inverse problem solving scheme, which (i) sequentially determines the parameters of interest, layer by layer, in a 5-layer skin model using (ii) a custom cost-function adapted to the layered structure of the skin, i.e. considering wavelength and source-detector distance sensitivity to each layer. In-silico validation of the proposed approach was performed through convergence analysis towards ground truth simulated spectra. Using this sequential approach, the values of a 4-parameters vector were estimated with a relative errors of a few percents only and three times faster compared to current optimization method. Moreover, it brings morphological and physiological dimension to the inverse problem solving.