The model-based reconstruction algorithm is adopted in order to conquer the ill-posedness in optical tomography.An edge-preserving

global smoothing generalized Gaussian Markov random field(GGMRF) is imported into optical tomography reconstruction based on the radiative transfer equation in this paper.The iteration optimization method is used to solve the objective function with the GGMRF model by maximizing the a posterior probability

but the gradient computation of the objective function with respect to optical parameters is difficult.Therefore

a novel gradient computation strategy based on gradient tree is proposed.Experimental results show that this kind of reconstruction technology can improve the image reconstruction quality and decrease the ill-posedness compared to the reconstruction algorithm without priori model.