An overview on recent radiation transport algorithm development for optical tomography imaging

Optical properties reconstruction using the adjoint method based on the radiative transfer equation

“…This is because the OF converges around a certain noisy value. This computational feature is often encountered for gradient based algorithms and has been reported in [10,36]. It should be noted here that the estimation of g would have not been possible with the diffusion approximation.…”

“…Therefore, this factor can provide a potential contrast agent for optical medical diagnosis between healthy and tumoral tissues. To our best knowledge, up to now, no works have been done to investigate the reconstruction of the spatial distribution of g [10]. On the other hand, an efficient forward model to predict light transport in the biological tissue is required in order to estimate optical parameters.…”

Near infra-red imaging with the radiative transfer equation: A comparative study with finite elements

“…We have developed so far a number of reconstruction algorithms for optical tomography applications with numerical models based on the radiative transfer equations in steady, frequency and time domains [1,3,6,7,8]. As for optimization, robust algorithms of gradient type have been developed and coupled with the adjoint method for the computation of the objective function gradient, among which we can name the conjugate gradient without line search, the sensitive function conjugate gradient [9].…”

Optical tomography with discretized path integral

“…Optical tomography with discretized path integral Bingzhi Optical tomography [1][2][3][4][5][6][7][8] is known as a safer alternative to x-ray tomography. Usually, tomography consists of a light source generating penetrative light and a detector capturing the light, which allows to estimate the inside of the object through which the light is passing.…”