Sub-diffusive scattering parameter maps recovered using wide-field high-frequency structured light imaging

Abstract. To detect small-scale changes in tissue with optical techniques, small sampling volumes and, therefore, short source-detector separations are required. In this case, reflectance measurements are not adequately described by the diffusion approximation. Previous studies related subdiffusive reflectance to γ or σ, which parameterize the phase function. Recently, it was demonstrated that σ predicts subdiffusive reflectance better than γ, and that σ becomes less predictive for lower numerical apertures (NAs). We derive and evaluate the parameter R pNA , which incorporates the NA of the detector and the integral of the phase function over the NA in the backward and forward directions. Monte Carlo simulations are performed for overlapping source/detector geometries for a range of phase functions, reduced scattering coefficients, NAs, and source/detector diameters. R pNA improves prediction of the measured reflectance compared to γ and σ. It is, therefore, expected that R pNA will improve derivation of optical properties from subdiffusive measurements. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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“…[7][8][9][10] However, recent work showed that a range of γ values (for the same μ 0 s , μ a , and d det ) can result in the same reflectance.…”

Section: Introductionmentioning

confidence: 99%

Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture

et al. 2017

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“…3 and 4, the RRE significantly depends on the numerical sampling method and underlying lookup table size. This suggests that special care should be taken when implementing the phase functions in the MC simulations, and moreover, include the information in research articles as this was not a common practice to date [4][5][6][7]10,11].…”

Section: Discussionmentioning

confidence: 99%

“…The anisotropy factor g can be found to be as low as 0.4 [24] and can reach values of up to 0.98 [25] in the biological tissues. With respect to parameter γ, the values tend to lie between 1.1 and 2.3 [6,26,27]. As a result, we have utilized 15 phase functions listed in Table 1.…”

Section: Phase Functions Utilized For Evaluating the Numerical Samplimentioning

confidence: 99%

“…In terms of Monte Carlo (MC) simulations, which are often used for modeling the light propagation [1,2], scattering is described by the scattering coefficient and scattering angle typically drawn from the inverse cumulative distribution of the phase function. In recent studies, phase functions have become increasingly important in modeling of the reflectance obtained by spatially-resolved reflectance spectroscopy [3][4][5] or spatial-frequency domain reflectance spectroscopy [6][7][8], in particular for small source-detector separations or high spatial frequencies. The Henyey-Greenstein (HG) phase function [9] is most commonly used in the biomedical community since it offers an analytical inverse of the cumulative distribution function (CDF), which is convenient for sampling the scattering angles by a random number drawn from a uniform distribution.…”

Section: Introductionmentioning

confidence: 99%

“…From our experience, we have noticed that the number of the tabulated CDF values as well as the sampling method applied to the phase function can significantly influence the accuracy of the MC simulated reflectance. Most of the studies that have used numerical phase function sampling as described above, lack the information on the details of the employed sampling method [4][5][6][7]10,11]. Consequently, it is very difficult to properly repeat the experiments conducted in those studies.…”

Section: Introductionmentioning

confidence: 99%

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Analytical expressions for sampling the scattering angle from a phase function in Monte Carlo simulations of light propagation are available only for a limited number of phase functions. Consequently, numerical sampling methods based on tabulated values are often required instead. By using Monte Carlo simulated reflectance, we compare two existing and propose an improved numerical sampling method and show that both the number of the tabulated values and the numerical sampling method significantly influence the accuracy of the simulated reflectance. The provided results and guidelines should serve as a good starting point for conducting computationally efficient Monte Carlo simulations with numerical phase function sampling.

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Sub-diffusive scattering parameter maps recovered using wide-field high-frequency structured light imaging

Cited by 74 publications

References 50 publications

Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture

Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture

Lookup table-based sampling of the phase function for Monte Carlo simulations of light propagation in turbid media

Image-derived arterial input function for quantitative fluorescence imaging of receptor-drug binding in vivo

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