Fast localize the bioluminescent source via graph cuts

Abstract

Bioluminescence imaging (BLI) and bioluminescence tomography (BLT) make it possible to elucidate cellular signatures to better understand the effects of human disease in small animal in vivo. However, to the best of our knowledge, the existing gradient-type reconstruction methods in BLT are not very efficient, and often require a relatively small volume of interest (VOI) for feasible results. In this paper, a fast graph cuts based reconstruction method for BLT is presented, which is to localize the bioluminescent source in heterogeneous mouse atlas via max-flow/min-cut algorithm. Since the original graph cuts theory can only handle graph-representable problem, the quadratic pseudo-boolean optimization is incorporated to make the graph tractable. The internal light source can be reconstructed from the whole domain, so a priori knowledge of VOI can be avoided in this method. In the experiments, the proposed method is validated in a heterogeneous mouse atlas, and the source can be localized reliably and efficiently by graph cuts; and compared with a gradient-type method, graph cuts is about 25–50 times faster.