Lp Regularization For Bioluminescence Tomography Based On Split Bregman

Molecular imaging is an imaging technology which demonstrate specific molecular, cellular and subcellular activity, reflecting the molecular changes in vivo. It could quantitatively research the biological behavior in terms of image science. BLT can provide experimental basis and necessary theoretical for early cancer detection and anticancer drug development, and it is also a main part for multi-modal and multi-dimensional imaging. The conventional reconstruction algorithm has been proposed to improve the accuracy and efficiency of BLT. In this paper, we proposed the Lp-norm techniques based on Split-Bregman algorithm, which combine the bioluminescence imaging with micro CT. Numerical simulation is performed to validated the proposed method, and the results prove that the proposed method can achieve more accurate reconstruction result with less computation time, without any a prior condition like the feasible region.In this paper Split Bregman method based on the Lp norm which is used for bioluminescence tomography imaging. The proposed method can distinguish the mice subcutaneous tumor area for noninvasive in vivo detection. BLT is a promising optical imaging technique in preclinical research at molecular levels. The problem of BLT reconstruction is quite ill-posed and ill-conditioned. In order to achieve high accuracy for its inverse reconstruction, we proposed a novel approach based on Lp regularization with the Split Bregman method. The diffusion equation was used as the forward model. Then, we defined the objective function of Lp regularization to optimize this function. After that, we conducted numerical simulations and in vivo experiments to evaluate the accuracy and efficiency of the proposed method. The results of the simulations indicated that compared with the conjugate gradient and iterative shrinkage methods, the proposed method is more accurate and faster for multi-source reconstructions. Furthermore, in vivo imaging suggested that it could clearly distinguish the viable and apoptotic tumor regions. The Split Bregman iteration method can achieve accurate reconstruction in BLT.