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Quantifying the optical properties and chromophore concentrations of turbid media by chemometric analysis of hyperspectral diffuse reflectance data collected using a fourier interferometric imaging system

机译：通过使用傅里叶干涉成像系统收集的高光谱漫反射数据的化学计量分析来量化混浊介质的光学性质和发色团浓度

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A non-contact Fourier transform interferometric imaging system was used to collect hyperspectral images of the steady-state diffuse reflectance from a point source in turbid media for the spectral range of 550-850 nm. Steady-state diffuse reflectance profiles were generated from the hyperspectral images, and partial least-squares (PLS) regression was performed on the diffuse reflectance profiles to quantify absorption (mu (alpha)) and reduced scattering (mu (s)') properties of turbid media. The feasibility of using PLS regression to predict optical properties was examined for two different sets of spatially-resolved diffuse reflectance data. One set of data was collected from 40 turbid phantoms, while the second set was generated by convolving Monte Carlo simulations with the instrument response of the imaging system. Study results show that PLS prediction of mu (alpha) and mu (s)' was accurate to within +/-8% and +/-5%, respectively, when the model was trained on turbid phantom data. Moreover, PLS prediction of optical properties was considerably faster and more efficient than direct least-squares fitting of spatially-resolved profiles. When the PLS model was trained on Monte Carlo simulated data and subsequently used to predict mu (alpha) and mu (s)' from the diffuse reflectance of turbid phantom, the percent accuracies degraded to +/-12% and +/-5%, respectively. These accuracy values are applicable to homogenous, semi-infinite turbid phantoms with optical property ranges comparable to tissues.
机译：非接触式傅里叶变换干涉成像系统用于收集浊点介质中点源在550-850 nm光谱范围内稳态扩散反射的高光谱图像。从高光谱图像生成稳态漫反射率曲线，并对漫反射率曲线执行偏最小二乘（PLS）回归，以量化其的吸收（mu（α））和减少的散射（mu（s）'）特性。浑浊的介质。对于两组不同的空间分辨漫反射数据，检查了使用PLS回归预测光学特性的可行性。从40个浑浊的体模中收集了一组数据，而第二组数据是通过将蒙特卡洛模拟与成像系统的仪器响应进行卷积生成的。研究结果表明，当对模型进行混浊的幻象数据训练时，μ（α）和μ（s）'的PLS预测分别精确到+/- 8％和+/- 5％之内。此外，光学特性的PLS预测比空间分辨轮廓的直接最小二乘拟合要快得多，效率也更高。当在蒙特卡洛模拟数据上训练PLS模型并随后用于根据混浊体模的漫反射率预测mu（alpha）和mu（s）'时，准确度百分比降低到+/- 12％和+/- 5％ ， 分别。这些精度值适用于光学特性范围与组织相当的均质，半无限浑浊体模。

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