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Journal Article
Research Support, Non-U.S. Gov't
Reconstruction Method for In Vivo Bioluminescence Tomography Based on the Split Bregman Iterative and Surrogate Functions.
Molecular Imaging and Biology : MIB : the Official Publication of the Academy of Molecular Imaging 2017 April
PURPOSE: Bioluminescence tomography (BLT) can provide in vivo three-dimensional (3D) images for quantitative analysis of biological processes in preclinical small animal studies, which is superior than the conventional planar bioluminescence imaging. However, to reconstruct light sources under the skin in 3D with desirable accuracy and efficiency, BLT has to face the ill-posed and ill-conditioned inverse problem. In this paper, we developed a new method for BLT reconstruction, which utilized the mathematical strategies of the split Bregman iterative and surrogate functions (SBISF) method.
PROCEDURES: The proposed method considered the sparsity characteristic of the reconstructed sources. Thus, the sparsity itself was regarded as a kind of a priori information, and the sparse regularization is incorporated, which can accurately locate the position of the sources. Numerical simulation experiments of multisource cases with comparative analyses were performed to evaluate the performance of the proposed method. Then, a bead-implanted mouse and a breast cancer xenograft mouse model were employed to validate the feasibility of this method in in vivo experiments.
RESULTS: The results of both simulation and in vivo experiments indicated that comparing with the L1-norm iteration shrinkage method and non-monotone spectral projected gradient pursuit method, the proposed SBISF method provided the smallest position error with the least amount of time consumption.
CONCLUSIONS: The SBISF method is able to achieve high accuracy and high efficiency in BLT reconstruction and hold great potential for making BLT more practical in small animal studies.
PROCEDURES: The proposed method considered the sparsity characteristic of the reconstructed sources. Thus, the sparsity itself was regarded as a kind of a priori information, and the sparse regularization is incorporated, which can accurately locate the position of the sources. Numerical simulation experiments of multisource cases with comparative analyses were performed to evaluate the performance of the proposed method. Then, a bead-implanted mouse and a breast cancer xenograft mouse model were employed to validate the feasibility of this method in in vivo experiments.
RESULTS: The results of both simulation and in vivo experiments indicated that comparing with the L1-norm iteration shrinkage method and non-monotone spectral projected gradient pursuit method, the proposed SBISF method provided the smallest position error with the least amount of time consumption.
CONCLUSIONS: The SBISF method is able to achieve high accuracy and high efficiency in BLT reconstruction and hold great potential for making BLT more practical in small animal studies.
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