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The inverse problem of fluorescence diffuse optical tomography (FDOT) is often highly ill-posed, which needs regularization techniques. In this paper, we propose a combined l1-l2-norm regularization method to address the ill-posed FDOT inverse problem. Compared with the traditional Tikhonov regularization, the proposed method is able to effectively remove the noise in the reconstructed image without much over-smoothness. The performance of the proposed method is demonstrated in 3D numerical simulation.