An effective forward model based on accelerated Monte Carlo method for diffusion optical tomography imaging systems

In noninvasive tomography, subcutaneous abnormal tissue can change the absorption coefficient of light. This paper explores diffusion optical tomography. It uses the amount of incident light diffusing to the surface of the skin to detect light intensity at a specific position. The specific reconstruction algorithm is used to reconstruct the distribution of abnormal tissue in detection areas. This paper proposes a forward model for diffusion optical tomography. Based on an accelerated Monte Carlo method, the forward model saves simulation time when detecting light propagation in subcutaneous tissue. This technique is used to examine the reconstruction algorithm to evaluate abnormal tissue distribution accuracy.