A grid-based method is presented to extract tetrahedral meshes from the preprocessed volume data, during which the isosurface representing the domain boundary is extracted and the volume inside the domain is tetrahedralized. After the medical volume data is organized into an invisible background grid, a dual method is employed to construct a continuous triangular surface that piecewise linearly approximates the isosurface. To fill the isosurface with tetrahedra, cubes either intersecting with or lying within the isosurface are decomposed by using the precomputed stencils. Finally, Laplacian smoothing is conducted to improve the overall quality of the generated tetrahedral meshes. Regarding that the numerical analysis demands reduced number of elements and accurate geometry near the boundary, adaptive meshing method based on octree-structured grid is also explored. Example of meshing the human distal femur from CT scans is presented, which is applied in the virtual arthroscopic knee surgery.