17 May 2016 A sequential method for measuring the optical properties of two-layer media with spatially-resolved diffuse reflectance: simulation study
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Abstract
A sequential method for estimating the optical properties of two-layer media with spatially-resolved diffuse reflectance was proposed and validated using Monte Carlo-generated reflectance profiles. The relationship between the penetration depth of detected photons and source-detector separation was first studied. Photons detected at larger source-detector separations generally penetrated deeper into the medium than those detected at small source-detector separations. The effect of each parameter (i.e., the absorption and reduced scattering coefficients (μa and μs) of each layer, and the thickness of top layer) on reflectance was investigated. It was found that the relationship between the optical properties and thickness of top layer was a critical factor in determining whether photons would have sufficient interactions with the top layer and also penetrate into the bottom layer. The constraints for the proposed sequential estimation method were quantitatively determined by the curve fitting procedure coupled with error contour map analyses. Results showed that the optical properties of top layer could be determined within 10% error using the semi-infinite diffusion model for reflectance profiles with properly selected start and end points, when the thickness of top layer was larger than two times its mean free path (mfp’). And the optical properties of the bottom layer could be estimated within 10% error by the two-layer diffusion model, when the thickness of top layer was less than 16 times its mfp’. The proposed sequential estimation method is promising for improving the estimation of the optical properties of two-layer tissues from the same spatially-resolved reflectance.
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Aichen Wang, Aichen Wang, Renfu Lu, Renfu Lu, Lijuan Xie, Lijuan Xie, } "A sequential method for measuring the optical properties of two-layer media with spatially-resolved diffuse reflectance: simulation study", Proc. SPIE 9864, Sensing for Agriculture and Food Quality and Safety VIII, 98640Q (17 May 2016); doi: 10.1117/12.2225104; https://doi.org/10.1117/12.2225104
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