An image reconstruction method for mesoscopic fluorescence molecular tomography with the level-by-level reduced system

Computational complexity is a big challenge for reconstruction of mesoscopic fluorescence molecular tomography (MFMT). In this work, a new method is proposed to reconstruct the image for MFMT with the reduced system. The inverse problem is solved with the Schur complement system level by level to improve the computational efficiency. Further, in order to improve the ill-posedness of the inverse problem, the spatially variant regularization parameter is employed in the process of solving the inverse problem. The simulation results demonstrate that both of the reconstruction speed and accuracy can be improved.