基于改进标准漫射近似模型的生物组织光学参数反演

邢永春; 朱启兵; 黄敏

doi:doi:10.3788/lop53.091701

激光与光电子学进展, 2016, 53 (9): 091701, 网络出版: 2016-09-14

基于改进标准漫射近似模型的生物组织光学参数反演下载： 533次

Inversion of Optical Parameters of Biological Tissues Based on Improved Standard Diffusion Approximation Model

论文大纲

邢永春 ^*朱启兵黄敏

作者单位

江南大学物联网工程学院轻工过程先进控制教育部重点实验室, 江苏无锡 214122

生物光学改进标准漫射近似参数反演光学参数误差 biotechnology improved standard diffusion approximation parameter inversion optical parameters error

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摘要

针对标准漫射近似模型受限于接近各向同性光辐射以及光源-探测器距离远大于一个输运平均自由程的问题，提出了一种改进标准漫射近似模型。该模型在空气-生物组织边界处引入另一个点源，减小了近光源处的误差。分析了各向异性因子和μ′s/μa(μ′s为有效散射系数，μa为吸收系数)比值对漫反射分布的影响，并结合非线性最小二乘算法对光学特性参数μa、μ′s进行了反演求解。结果表明，与标准漫射近似模型相比，改进模型可显著减小漫反射分布曲线误差，提高反演精度。改进模型的反演精度接近双点源Delta-P1近似模型，同时能较好地克服后者反演参数重复性较差的缺点。

Abstract

Aiming at the nearly isotropic optical radiation and source-detector separation that is much longer than one transport mean free path in the standard diffusion approximation model, an improved model is developed by adding a point source at the air-biological tissue boundary to minimize the error close to the light source. The effect of anisotropy and the ratio of μ′s/μa on diffuse distribution is analyzed, where μ′s is the effective scattering coefficient and μa is the absorption coefficient. The inversions of the optical parameters μa and μ′s are solved by using the improved model combining the nonlinear least squares method. The results show that compared with the standard diffusion approximation model, the improved model can reduce the error of diffuse distribution curve significantly and improve the inversion accuracy. The improved model provides similar inversion accuracy to the two-point source Delta-P1 approximation model and has no poor reproducibility of inversion parameters exhibited by the latter.

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邢永春, 朱启兵, 黄敏. 基于改进标准漫射近似模型的生物组织光学参数反演[J]. 激光与光电子学进展, 2016, 53(9): 091701. Xing Yongchun, Zhu Qibing, Huang Min. Inversion of Optical Parameters of Biological Tissues Based on Improved Standard Diffusion Approximation Model[J]. Laser & Optoelectronics Progress, 2016, 53(9): 091701.

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