Literature DB >> 12790437

Hybrid Monte Carlo-diffusion method for light propagation in tissue with a low-scattering region.

Toshiyuki Hayashi1, Yoshihiko Kashio, Eiji Okada.   

Abstract

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

Mesh:

Year:  2003        PMID: 12790437     DOI: 10.1364/ao.42.002888

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  13 in total

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Review 10.  Recent methodology advances in fluorescence molecular tomography.

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