Fluorescence molecular tomography (FMT) is an imaging technique that can localize and quantify fluorescent markers to resolve\nbiological processes at molecular and cellular levels. Owing to a limited number ofmeasurements and a large number of unknowns\nas well as the diffusive transport of photons in biological tissues, the inverse problem in FMT is usually highly ill-posed. In this\nwork, a sparsity-constrained preconditioned Kaczmarz (SCP-Kaczmarz) method is proposed to reconstruct the fluorescent target\nfor FMT.The SCP-Kaczmarz method uses the preconditioning strategy to minimize the correlation between the rows of the forward\nmatrix and constrains the Kaczmarz iteration results to be sparse.Numerical simulation and phantomand in vivo experiments were\nperformed to test the efficiency of the proposed method. The results demonstrate that both the convergence and accuracy of the\nproposed method are improved compared with the classical memory-efficient low-cost Kaczmarz method.
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