Time Resolved Analysis of Continuous Wave MC Photon Fluencies

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ICONTES 2018 International Conference on Technology, Engineering and Science, Antalya, Turkey, 26 - 29 October 2018, pp.38

  • Publication Type: Conference Paper / Full Text
  • City: Antalya
  • Country: Turkey
  • Page Numbers: pp.38
  • Akdeniz University Affiliated: Yes


 Time dependent (TD) Monte Carlo (TDMC) photon-tissue interactions simulation program code generated photon fluencies (Joule/cm²) for ten picosecond (ps) time series [100 , 200,  … 1000] for Continuous Wave (CW) laser source. TD MC ANSI Standard C program code “trmc.c” was modified and compiled to generate photon fluence distributions inside the imaging tissue model. Cylindrical coordinate system was chosen to compile the ANSI standard C based photon walk program code. Radial r, and depth z axis created cylindrical mesh grid (r, z) array. Collimated isotropic point laser source within a semi-infinite homogeneous medium was used. Radial diameter of cylindrical coordinate system 2r = 6.0 cm, depth z = 3.0 cm. In this study, TD analysis of CW MC photon fluencies for the photon-tissue interactions simulation mesh grid geometry for Nz = 30, and Nr = 30 dimensions within 3 cm x 6 cm was performed. In the MC simulation program code, the tissue absorption and scattering coefficients were chosen as ma = 0, and ms = 100 cm-1. 60.000 photons were sent into the tissue from (x, y, z) = (3.0, 3.0, 3.0) cm isotropic laser source position. The values of photon fluencies are varying depend on the time in tissue environment were recorded in the ANSI standard C program data output file. The time intervals were chosen by 100 picosecond (ps) steps, from 100 ps to 1000 ps sequentially. Depend on the increasing time steps, CW photon migration was observed inside the tissue, successfully. TD analysis of CW photon fluencies will be used when making the time resolved diffuse optic tomography (TRDOT) device. Forward model problem weight matrix will be built based on the TD distributions of MC photon fluencies, then photon fluencies will be used in the inverse problem solution image reconstruction algorithm. The location of buried inclusions will be determined.