Abstract
This paper introduces an improved diffusion model which is accurate and fast in computation for the cases of mu(a)/mu'(s) < 0.07 as good as the conventional diffusion model for the cases of mu(a)/mu'(s) < 0.007 for surface measurement, hence more suitable than the conventional model to be the forward model used in the image reconstruction in the diffuse optical tomography. Deviation of the diffusion approximation (DA) on the medium surface is first studied in the Monte Carlo (MC) diffusion hybrid model for reflectance setup. A modification of DA and an improved MC diffusion hybrid model based on this modified DA are introduced. Numerical tests show that for media with relatively strong absorption the present modified diffusion approach can reduce the surface deviation significantly in both the hybrid and pure diffusion model, and consumes nearly no more computation time than the conventional diffusion approach.
Highlights
Diffuse optical tomography (DOT) [1,2] using near-infrared light can image the optical properties of biological tissues non-invasively, is used and promising in many biomedical applications such as breast cancer detection [3] and functional brain imaging [4,5]
Hybrid models that use the diffusion model in the far-fromsource region and an accurate model in the near-source region was proposed, e.g., Monte Carlo diffusion hybrid model (MC simulation is used in the near-source region) [14,15,16] and transport diffusion hybrid model [17,18]
We introduce an improved diffusion model which is accurate and fast in computation for the cases of μa/μ’s < 0.07 as good as the conventional diffusion model for the cases of μa/μ’s < 0.007 for surface measurement, more suitable than the conventional model to be the forward model used in the DOT image reconstruction
Summary
Diffuse optical tomography (DOT) [1,2] using near-infrared light can image the optical properties of biological tissues non-invasively, is used and promising in many biomedical applications such as breast cancer detection [3] and functional brain imaging [4,5]. The radiance transport equation (RTE) [6] and Monte Carlo (MC) simulation [7,8,9] are two accurate models for light propagation in turbid medium Both the two models are time-consuming not suitable to be the forward model for the DOT image reconstruction. The first limitation is that the medium must be scattering dominated (i.e., the ratio of the absorption coefficient over the reduced scattering coefficient must be much less than 1, e.g., when μa / μ’s ≤ 0.005, the deviation of the DE solution from the RTE solution is usually smaller than 1%) Another limitation of DE is that it can not correctly model light propagation in the “near-source region” (the region near the incident point of the collimated light source) [10,11,12,13].
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