In this study, a hybrid-model imaging system combining fluorescence and ultrasound (US) was investigated with the
motivation of providing structural priors towards improvement of fluorescence reconstruction. A single element
transducer was scanned over the sample for anatomy. In the fluorescence part, a laser source was scanned over the
sample with the emission received by an EMCCD camera. Synchronization was achieved by a pair of motorized linear
stages. Structural information was derived from the US images and a profilometry and used to constrain reconstruction.
In the reconstruction, we employed a GPU-based Monte Carlo simulation for forward modeling and a pattern-based
method to take advantage of the huge dataset for the inverse problem. Performance of this system was validated with two
phantoms with fluorophore inclusions. The results indicated that the fluorophore distribution could be accurately
reconstructed. And the system has a potential for the future in-vivo study.