中文摘要：

无创测量确定生物组织的光学特性参数在医学诊断和治疗领域中有着广泛的应用前景。目前确定组织参数的方法多建立在单层模型条件下，而实际的许多生物组织均具有分层结构，比如在肌肉、颅骨等。因此在多层模型条件下反演计算组织参数具有更大的实际意义。近年许多研究者针对以上问题提出了各种解决方法，如最小二乘法、神经网络方法等，但这些方法都存在需要时间过长或者误差较大的缺点。本文在组织参数测量领域引入数据挖掘办法——支持向量机（support vector machines，SVM），对双层模型中四个待定组织光学参数的确定进行了研究。结果表明。利用SVM方法确定组织光学参数具有很好的准确性和实时性。

英文摘要：

Noninvasive determination of tissue optical properties is essential for clinical applications in medical diagnostics and therapeutics. In this paper, we introduced an efficient method to determine the optical properties of the two-layer medium from the steady-state spatially resolved diffuse reflectance, which is based on the theory of support vector machine （SVM）. The method was validated using the Monte Carlo algorithm generated reflectance from a two-layer model that consists of an infinite top layer and a semi-infinite bottom layer. The training and predicting time of SVM are 35s and 5s respectively. The predictive errors of the proposed method were less than 3% for the top-layer optical properties and less than 6% for the bottom-layer optical properties based on RBF kernel, showing that the SVM method is a more efficient way for real-time clinical applications than other methods.