Archive | 2019
Robust reconstruction of fluorescence molecular tomography based on a two-stage matching pursuit method for in vivo orthotopic hepatocellular carcinoma xenograft mouse model
Abstract
As a promising tomographic method in preclinical research, fluorescence molecular tomography (FMT) can obtain real-time three-dimensional (3D) visualization for in vivo studies. However, because of the ill-posed nature and sensitivity to noise of the inverse problem, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this study, we present a two-stage matching pursuit (TSMP) method. The iterative process is divided into two processes: In the first stage, we iterate several times using the OMP algorithm to improve the accuracy of the support set, which is because most of the atoms selected by the OMP algorithm are accurate. In the second stage, we use CoSaMP algorithm to iterative. The initial input of the second stage is the residual and atom obtained by the first stage OMP algorithm, which can change the dependence of CoSaMP to sparsity. Meanwhile, considering the time of reconstruction, we set the iterative times of the first stage to K/2 (K is the sparisty). Because of the accuracy of the initial output and the choice of atomic criteria, the proposed algorithm has better performance than OMP and CoSaMP algorithm. The result of numerical simulation show that TSMP method can not only achieves accurate and desirable fluorescent source reconstruction, but also demonstrates enhanced robustness to noise.