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Light Transport in Turbid Media with Non-scattering, Low-scattering and High Absorption Heterogeneities Based on Hybrid Simplified Spherical Harmonics with Radiosity Model

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Specialty Radiology
Date 2013 Oct 25
PMID 24156077
Citations 6
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Abstract

Modeling light propagation in the whole body is essential and necessary for optical imaging. However, non-scattering, low-scattering and high absorption regions commonly exist in biological tissues, which lead to inaccuracy of the existing light transport models. In this paper, a novel hybrid light transport model that couples the simplified spherical harmonics approximation (SPN) with the radiosity theory (HSRM) was presented, to accurately describe light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities. In the model, the radiosity theory was used to characterize the light transport in non-scattering regions and the SPN was employed to handle the scattering problems, including subsets of low-scattering and high absorption. A Neumann source constructed by the light transport in the non-scattering region and formed at the interface between the non-scattering and scattering regions was superposed into the original light source, to couple the SPN with the radiosity theory. The accuracy and effectiveness of the HSRM was first verified with both regular and digital mouse model based simulations and a physical phantom based experiment. The feasibility and applicability of the HSRM was then investigated by a broad range of optical properties. Lastly, the influence of depth of the light source on the model was also discussed. Primary results showed that the proposed model provided high performance for light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities.

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References
1.
Gibson A, Hebden J, Arridge S . Recent advances in diffuse optical imaging. Phys Med Biol. 2005; 50(4):R1-43. DOI: 10.1088/0031-9155/50/4/r01. View

2.
Hayashi T, Kashio Y, Okada E . Hybrid Monte Carlo-diffusion method for light propagation in tissue with a low-scattering region. Appl Opt. 2003; 42(16):2888-96. DOI: 10.1364/ao.42.002888. View

3.
Tian J, Bai J, Yan X, Bao S, Li Y, Liang W . Multimodality molecular imaging. IEEE Eng Med Biol Mag. 2008; 27(5):48-57. DOI: 10.1109/MEMB.2008.923962. View

4.
Klose A . The forward and inverse problem in tissue optics based on the radiative transfer equation: a brief review. J Quant Spectrosc Radiat Transf. 2010; 111(11):1852-1853. PMC: 2895669. DOI: 10.1016/j.jqsrt.2010.01.020. View

5.
Chen X, Yang D, Qu X, Hu H, Liang J, Gao X . Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection. J Biomed Opt. 2012; 17(6):066015. DOI: 10.1117/1.JBO.17.6.066015. View