Bioluminescence tomography with structural information estimated via statistical mouse atlas registration

Due to an ill-posed and underestimated characteristic of bioluminescence tomography (BLT) reconstruction, a priori anatomical information obtained from computed tomography (CT) or magnetic resonance imaging (MRI), is usually incorporated to improve the reconstruction accuracy. The organs need to be segmented, which is time-consuming and challenging, especially for the low-contrast CT images. In this paper, we present a BLT reconstruction method based on a statistical mouse atlas to improve the efficiency of heterogeneous model generation and the accuracy of target localization. The low-contrast CT image of the mouse was first registered to the statistical mouse atlas model with the constraints of mouse surface and high-contrast organs (bone and lung). Then the other organs, such as the liver and kidney, were determined automatically through the statistical mouse atlas model. The estimated organs were then discretized into tetrahedral meshes for BLT reconstruction. The linearized Bregman method was used to solve the sparse inverse problem of BLT by minimizing the regularization function (L1 norm plus L2 norm with smooth factor). Both numerical simulations and in vivo experiments were conducted, and the results demonstrate that even though the localization of the estimated organs may not be exactly accurate, the proposed method is feasible to reconstruct the bioluminescent source effectively and accurately with the estimated organs. This method would greatly benefit the bioluminescent light source localization for hybrid BLT/CT systems.