TY  - JOUR
T1  - Forward Problem Model Neighborhood Relations Based on the Monte Carlo (MC) Simulation Photon Fluence Distributions
AU  - Kazancı, Huseyin Ozgur
PY  - 2018
DA  - December
JF  - The Eurasia Proceedings of Science Technology Engineering and Mathematics
JO  - EPSTEM
PB  - ISRES Publishing
WT  - DergiPark
SN  - 2602-3199
SP  - 8
EP  - 14
IS  - 4
LA  - en
AB  - Forwardproblem model was created for the continuous wave (CW) biomedical diffuse opticimaging (DOI) modality. Forward problem model weight matrix functions werecalculated based on the photon’s Monte Carlo (MC) particle simulation model.Photon was thought as a particle, scattering and absorption events were actedinside the imaging tissue model. Doing this work has two main parts, the firstpart is running MC simulation program, the second part is transferring MCphoton fluencies from ANSI Standard C programming environment to the imagereconstruction platform, then translating or interpolating the photon fluencedistributions based on the imaging tissue mesh grid geometry, finally buildingthe forward problem model weight matrix by multiplying photon fluencies undereach source and detector positions. MC photon propagation code was run forseven-layer head model in ANSI standard C programming compiler under the Cygwinprompt. Absorption (µa), and scattering (µs) tissue opticcoefficients were selected as tough to mimic human head. Multi sources anddetectors were placed on imaging tissue, which is slab back-reflected geometry.Between each source and detector positions, calculated MC photon fluencedistributions were transferred from ANSI standard C code output data andtranslated by mathematical interpolation method to image reconstruction programmesh grid geometry. In order to do that, multi-source and detector matches weregrouped into sub-classes. Each class has different source-detector distance(SDS) group. Forward problem model weight matrix functions were calculated anddrawn in xy bird-eye and yz side-view. They were observed as they were predicted,successfully. This work involves grouping the same neighborhood weightfunctions appropriately. 
KW  - Monte Carlo (MC) simulation photon fluencies
KW  - Forward model weight matrix
CR  - S.L. Jacques, https://omlc.org/classroom/ece532/class4/ssmc/index.html
Jacques, S.L. Monte Carlo Modeling of Light Transport in Tissue. Optical-Thermal Response of Laser-Irradiated Tissue pp 73-100, 1989.  
Cutler M. Transillumination as an aid in the diagnosis of breast lesions. Surg. Gynecol. Obstet. 48:721-8, 1929.                                                                   
Arridge S.R. Methods in diffuse optical imaging”. Phil. Trans. R. Soc. A 369, 4558–4576, 2011.
Arridge S.R. and Hebden J.C. Optical imaging in medicine: II. Modelling and reconstruction. Phys. Med. Biol. 42:841–853, 1997.                                                                                                                                   
Boas D.A., Gaudette T., A.S.R. Simultaneous imaging and optode calibration with diffuse optical tomography. Opt. Ex. 8:5,263-270, 2001.
Gibson A.P., Hebden J.C., and Arridge S.R. Recent advances in diffuse optical imaging. Phys. Med. Biol. 50, 2005.                  
Culver J.P. Statistical analysis of high density diffuse optical tomography. NeuroImage, 85:01, 2013.
UR  - https://dergipark.org.tr/en/pub/epstem/issue//492291
L1  - https://dergipark.org.tr/en/download/article-file/588636
ER  -