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 (µa), and scattering (µs) 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.
References
- 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.
Abstract
References
- 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.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | December 4, 2018 |
| Published in Issue | Year 2018Issue: 4 |
