A two-stage source reconstruction algorithm for bioluminescence tomography (BLT) is developed using hybrid finite element method (FEM). The proposed algorithm takes full advantages of linear and quadratic FEMs, which can be used to localize and quantify bioluminescent source accurately. In the first stage, a large permissible region is roughly determined and then iteratively evolved to reduce matrix dimension using efficient linear FEM. In the final stage, high-convergence quadratic FEM is applied to improve reconstruction result. Both numerical simulation and physical experiment are performed to evaluate the proposed algorithm. The relevant results demonstrate that quantitative reconstruction can be well achieved in terms of computation efficiency, source position, power density, and total power when compared with previous studies.
Monte Carlo （MC） method is a statistical method for simulating photon propagation in media in the optical molecular imaging field. However, obtaining an accurate result using the method is quite time-consuming, especially because the boundary of the media is complex. A voxel classification method is proposed to reduce the computation cost. All the voxels generated by dividing the media are classified into three types （outside, boundary, and inside） according to the position of the voxel. The classified information is used to determine the relative position of the photon and the intersection between photon path and media boundary in the MC method. The influencing factors and effectiveness of the proposed method are analyzed and validated by simulation experiments.
Adaptive finite element method （AFEM） is broadly adopted to recover the internal source in biological tissues. In this letter, a novel dual-mesh alternation strategy （dual-mesh AFEM） is developed for bioluminescence tomography. By comprehensively considering the error estimation of the finite element method solution on each mesh, two different adaptive strategies based on the error indicator of the reconstructed source and the photon flux density are used alternately in the process. Combined with the constantly adjusted permissible region in the adaptive process, the new algorithm can achieve a more accurate source location compared with the AFEM in the previous experiments.
