Forward Problem Model Neighborhood Relations Based on the Monte Carlo (MC) Simulation Photon Fluence Distributions

Abstract

Forward problem model was created for the continuous wave (CW) biomedical diffuse optic imaging (DOI) modality. Forward problem model weight matrix functions were calculated based on the photon’s Monte Carlo (MC) particle simulation model. Photon was thought as a particle, scattering and absorption events were acted inside the imaging tissue model. Doing this work has two main parts, the first part is running MC simulation program, the second part is transferring MC photon fluencies from ANSI Standard C programming environment to the image reconstruction platform, then translating or interpolating the photon fluence distributions based on the imaging tissue mesh grid geometry, finally building the forward problem model weight matrix by multiplying photon fluencies under each source and detector positions. MC photon propagation code was run for seven-layer head model in ANSI standard C programming compiler under the Cygwin prompt. Absorption (µ_a), and scattering (µ_s) tissue optic coefficients were selected as tough to mimic human head. Multi sources and detectors were placed on imaging tissue, which is slab back-reflected geometry. Between each source and detector positions, calculated MC photon fluence distributions were transferred from ANSI standard C code output data and translated by mathematical interpolation method to image reconstruction program mesh grid geometry. In order to do that, multi-source and detector matches were grouped into sub-classes. Each class has different source-detector distance (SDS) group. Forward problem model weight matrix functions were calculated and drawn in xy bird-eye and yz side-view. They were observed as they were predicted, successfully. This work involves grouping the same neighborhood weight functions appropriately. 

Keywords

• Monte Carlo (MC) simulation photon fluencies,Forward model weight matrix

References

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