Dam J S, Andersen P E, Dalgaard T, Fabricius P E
Appl Opt. 1998 Feb 1;37(4):772-8. doi: 10.1364/ao.37.000772.
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.
我们描述了一种从空间分辨漫反射中确定浑浊生物介质的约化散射系数和吸收系数的方法。采用一种Sugeno模糊推理系统结合数据预处理技术,对蒙特卡罗模拟生成的反射率数据进行多变量校准和预测。预处理包括主成分分析或源自扩散理论的一种新的扩展曲线拟合程序。对吸收系数在0.04至0.06 mm⁻¹之间且约化散射系数在0.45至0.99 mm⁻¹之间的反射率数据进行的预测测试表明,该方法对这两个系数的均方根误差均为0.25%。针对实际应用,我们还描述了使用相对而非绝对反射率数据、在反射率数据上施加测量噪声以及改变探测器数量和位置如何影响预测精度。