As a novel imaging modality,mesoscopic fluorescence molecular tomography (MFMT) can realize non-invasive high-resolution imaging for the distributi on of specific fluorescent probes in tumor tissues through image reconstruction al gorithms.However,MFMT reconstruction is a large-scale ill-posed and ill-conditioned inverse problem.Aiming at the problem of MFMT reconstruction,a method based on the simultaneous algebraic reconstruction technique is proposed.Firstly,the principal component analysis is utilized to double reduce the dimension of the sensitivity matrix to eliminate the redundant information.Then,the matrix obtained in the previous step is filled with zero to keep the consistency between the reconstruction result and the target data.Finally,the three-dimensional distribution of fluorescent probes is obtained through the simultaneous algebraic reconstruction technique with total variation regularization.To evaluate the performance of the proposed method,in silico and vascular tree experiments were carried out.Experimental results demonstrate that the proposed method can effectively shorten the reconstruction time,obtain high reconstruction accuracy and improve the performance of noise suppression.Therefore,the proposed method is suited for the MFMT reconstruction.