| Abstract: | We describe a method for determining the reduced scattering and absorption coefficients of turbid biological media from the spatially resolved diffuse reflectance. A Sugeno Fuzzy Inference System in conjunction with data preprocessing techniques is employed to perform multivariate calibration and prediction on reflectance data generated by Monte Carlo simulations. The preprocessing consists of either a principal component analysis or a new, extended curve-fitting procedure originating from diffusion theory. Prediction tests on reflectance data with absorption coefficients between 0.04 and 0.06 mm(-1) and reduced scattering coefficients between 0.45 and 0.99 mm(-1) show the root-mean-square error of this method to be 0.25% for both coefficients. With reference to practical applications, we also describe how the prediction accuracy is affected by using relative instead of absolute reflectance data, by imposing measurement noise on the reflectance data, and by changing the number and the position of detectors. |
