A novel method for determination of the optical properties of two-layer tissue model from spatially resolved diffuse reflectance
Ling Lin, Yaqin Chen, Gang Li, Jianming Gao, Kaijie Wu
Abstract
Ling Lin, Yaqin Chen, Gang Li, Jianming Gao, Kaijie Wu
Abstract
A novel method combining the PCA-NN algorithm established on the single-layer tissue model and the genetic algorithm based on the two-layer diffusion model has been presented to determine the optical properties of the two-layer medium from the steady-state spatially resolved diffuse reflectance. In detail, we firstly employ the PCA-NN algorithm established on the semi-infinite tissue model to extract the optical properties of the top layer from the spatially resolved reflectance that results from the photons migrating mainly within the top layer. With the knowledge of the optical properties of the top layer, the optical properties of the bottom layer are then obtained by use of the genetic algorithm for fitting the two-layer diffusion model to the reflectance data far from the source. The method was validated using the Monte Carlo generated reflectance for the two-layer medium of skin overlying fat or skin overlying muscle. And, the skin thickness was assumed to be known a priori and fixed at 5 mm. The results showed that all the optical properties of two layers can be determined by the method with the accuracy of better than 10%.
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A novel method combining the PCA-NN algorithm established on the single-layer tissue model and the genetic algorithm based on the two-layer diffusion model has been presented to determine the optical properties of the two-layer medium from the steady-state spatially resolved diffuse reflectance. In detail, we firstly employ the PCA-NN algorithm established on the semi-infinite tissue model to extract the optical properties of the top layer from the spatially resolved reflectance that results from the photons migrating mainly within the top layer. With the knowledge of the optical properties of the top layer, the optical properties of the bottom layer are then obtained by use of the genetic algorithm for fitting the two-layer diffusion model to the reflectance data far from the source. The method was validated using the Monte Carlo generated reflectance for the two-layer medium of skin overlying fat or skin overlying muscle. And, the skin thickness was assumed to be known a priori and fixed at 5 mm. The results showed that all the optical properties of two layers can be determined by the method with the accuracy of better than 10%.
Key concepts: Reflectivity, Layer (electronics), Diffuse reflection, Materials science, Diffuse reflectance infrared fourier transform, Diffusion, Monte Carlo method, Optics