Abstract
Fluorescence imaging is a target-specific molecular imaging technology using absorption coefficient of fluorophore. For this imaging model governed by an inverse problem for the coupled diffusion system, which describes the interaction of the excitation field from several boundary sources and the corresponding emission field, we reformulate it as an optimization problem. For solving this non-quadratic optimizing problem, we propose a decomposition scheme, which extracts the horizontal information of the target from the boundary measurement data directly. The realizability of this hybrid imaging scheme is rigorously proved mathematically for cubic and ellipsoid targets, by constructing an indicator function for the horizontal location of the target explicitly. Then based on this horizonal location as a good initial guess for the iteration process, the cost functional is optimized efficiently using the trust domain scheme. Numerical implementations are provided to show the validity of the proposed scheme.
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