Localization and quantification of the light sources generated by the expression of bioluminescent reporter genes is an important task in bioluminescent imaging of small animals, especially the generically engineered mice. To employ the Monte Carlo method for the light-source identification, the surfaces that define the anatomic structures of the small experimental animal is required; to perform finite element-based reconstruction computation, the volumetric mesh is a must. In this work, we proposed a Multiregional Marching Tetrahedra (MMT) method for extracting the surface and volumetric meshes from segmented CT/micro-CT (or MRI) image volume of a small experimental animal. The novel MMT method extracts triangular surface mesh and constructs tetrahedra/prisms volumetric finite element mesh for all anatomic components, including heart, liver, lung, bones etc., within one sweep over all the segmented CT slices. In comparison with the well-established Marching Tetrahedra (MT) algorithm, our MMT method takes into consideration of two more surface extraction cases within each tetrahedron, and guarantees seamless connection between anatomical components. The surface mesh is then smoothed and simplified, without losing the seamless connections. The MMT method is further enhanced to generate volumetric finite-element mesh to fill the space of each anatomical component. The mesh can then be used for finite element-based inverse computation to identify the light sources.