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从空间频域光谱和确定性辐射传输求解器中恢复层状组织的光学特性。

Recovery of layered tissue optical properties from spatial frequency-domain spectroscopy and a deterministic radiative transport solver.

机构信息

University of California, Department of Mathematics, Irvine, California, United States.

University of California, Beckman Laser Institute, Laser Microbeam and Medical Program, Irvine, Cali, United States.

出版信息

J Biomed Opt. 2018 Nov;24(7):1-11. doi: 10.1117/1.JBO.24.7.071607.

Abstract

We present a method to recover absorption and reduced scattering spectra for each layer of a two-layer turbid media from spatial frequency-domain spectroscopy data. We focus on systems in which the thickness of the top layer is less than the transport mean free path   (  0.1  -  0.8l  *    )  . We utilize an analytic forward solver, based upon the N'th-order spherical harmonic expansion with Fourier decomposition   (  SHEFN  )   method in conjunction with a multistage inverse solver. We test our method with data obtained using spatial frequency-domain spectroscopy with 32 evenly spaced wavelengths within λ  =  450 to 1000 nm on six-layered tissue phantoms with distinct optical properties. We demonstrate that this approach can recover absorption and reduced scattering coefficient spectra for both layers with accuracy comparable with current Monte Carlo methods but with lower computational cost and potential flexibility to easily handle variations in parameters such as the scattering phase function or material refractive index. To our knowledge, this approach utilizes the most accurate deterministic forward solver used in such problems and can successfully recover properties from a two-layer media with superficial layer thicknesses.

摘要

我们提出了一种从空间频域光谱数据中恢复双层混浊介质每层的吸收和散射光谱的方法。我们专注于顶层厚度小于输运平均自由程(0.1-0.8l * )的系统。我们利用基于 N 阶球谐展开和傅里叶分解的解析正向求解器(SHEFN)方法结合多阶段逆求解器。我们使用空间频域光谱在 λ = 450 到 1000nm 之间的 32 个等距波长对具有不同光学特性的六层组织模型进行了数据测试。我们证明,这种方法可以以与当前蒙特卡罗方法相当的精度恢复两层的吸收和散射系数光谱,但计算成本更低,并且具有潜在的灵活性,可以轻松处理散射相位函数或材料折射率等参数的变化。据我们所知,这种方法利用了此类问题中最准确的确定性正向求解器,并可以成功地从具有浅层厚度的两层介质中恢复性质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9a6/6995875/26cb8df8d653/JBO-024-071607-g001.jpg

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