June 2, 2023
S.Mohammad Motevalli

S.Mohammad Motevalli

Degree: Associate professor
Address: Department of Nuclear Physics, Faculty of Sciences, University of Mazandaran, P. O. Box 47415-416, Babolsar, Iran
Education: Ph.D in Nuclear physics
Phone: 01135302480
Faculty: Faculty of Science


Title Simulation of a fast diffuse optical tomography system based on radiative transfer equation
Type Article
radiative transport equation, NIR detector, absorption, scattering
Journal European Physical Journal Plus
DOI DOI 10.1140/epjp/i2016-16439-1
Researchers S.Mohammad Motevalli (First researcher) , Amir Payani (Second researcher)


Studies show that near-infrared (NIR) light (light with wavelength between 700nm and 1300nm) undergoes two interactions, absorption and scattering, when it penetrates a tissue. Since scattering is the predominant interaction, the calculation of light distribution in the tissue and the image reconstruction of absorption and scattering coefficients are very complicated. Some analytical and numerical methods, such as and Monte Carlo method, have been used for the simulation of light penetration in tissue. Recently, some investigators in the world have tried to develop a diffuse optical tomography system. In these systems, NIR light penetrates the tissue and passes through the tissue. Then, light exiting the tissue is measured by NIR detectors placed around the tissue. These data are collected from all the detectors and transferred to the computational parts (including hardware and software), which make a cross-sectional image of the tissue after performing some computational processes. In this paper, the results of the simulation of an optical diffuse tomography system are presented. This simulation involves two stages: a) Simulation of the forward problem (or light penetration in the tissue), which is performed by solving the diffusion approximation equation in the stationary state using FEM. b) Simulation of the inverse problem (or image reconstruction), which is performed by the optimization algorithm called Broyden quasi-Newton. This method of image reconstruction is faster compared to the other Newton-based optimization algorithms, such as the Levenberg-Marquardt one.