In small-animal molecular imaging, bioluminescence tomography (BLT) is used to reconstruct the internal bioluminescent source which can reveal the molecular and cellular information. Based on the general finite element tomographic method, the spatial resolution of source distribution need compromise between a priori fixed discretization degree to the given geometry domain and the computational cost of the reconstruction algorithm. In this contribution, an adaptive finite element methods based tomographic algorithm is represented and used to localize bioluminescent source. In the proposed algorithm, an initial coarse volumetric finite element mesh is provided and a priori knowledge is employed to determine the permissible source region. Furthermore, the local mesh refinement is performed to adaptively reduce the element size of the mesh by virtue of error estimation techniques. The above strategies reduce the ill-posedness of the BLT problem significantly and improve the numerical stability effectively. Numerical simulations with the homogeneous and heterogeneous phantoms, where the synthetic data is obtained through the adaptive finite element solver and Monte Carlo methods, show the effectiveness of the tomographic algorithm.
Bioluminescence tomography (BLT) is a novel technique in vivo which may localize and quantify bioluminescent
source to reveal the molecular and cellular information, and therefore it can monitor the growth and regression
of tumor non-invasively. In complicated biological tissue, the accuracy improvement of numerical solution to the
forward problem of BLT is beneficial to achieve better spatial resolution of source distribution. In this paper,
we introduce the adaptive FEMs framework based on the diffusion equation to enhance the solution accuracy of
the forward problem, and the bioluminescence imaging experiment has been performed with the heterogeneous
physical phantom which is also scanned by microCT scanner to generate the volumetric mesh as the initial finite
element mesh. Finally, The effectiveness of the adaptive FEMs framework is demonstrated with the comparison
between the experimental results and the simulation solution.
It is a challenging task to accurately describe complicated biological tissues and bioluminescent sources in bioluminescent imaging simulation. Several graphic editing tools have been developed to efficiently model each part of the bioluminescent simulation environment and to interactively correct or improve the initial models of anatomical structures or bioluminescent sources. There are two major types of graphic editing tools: non-interactive tools and interactive tools. Geometric building blocks (i.e. regular geometric graphics and superquadrics) are applied as non-interactive tools. To a certain extent, complicated anatomical structures and bioluminescent sources can be approximately modeled by combining a sufficient large number of geometric building blocks with Boolean operators. However, those models are too simple to describe the local features and fine changes in 2D/3D irregular contours. Therefore, interactive graphic editing tools have been developed to facilitate the local modifications of any initial surface model. With initial models composed of geometric building blocks, interactive spline mode is applied to conveniently perform dragging and compressing operations on 2D/3D local surface of biological tissues and bioluminescent sources inside the region/volume of interest. Several applications of the interactive graphic editing tools will be presented in this article.