Sparsity-promoting Bayesian approximation error method for compensating for the mismodeling of optical properties in fluorescence molecular tomography

In fluorescence molecular tomography, the quality of image reconstruction of fluorophore distribution is heavily reduced by the mismodeling of inaccurately known tissue optical properties. We propose an efficient sparsity-promoting Bayesian approximation error (spBAE) method to compensate for this mismodeling. The spBAE method incorporates sparsity prior into the BAE method by updating the parameters of the Gaussian prior according to its initial solution. In vivo experiments demonstrate that this new method greatly improves the reconstruction quality.