There is a need for the development of finite element (FE) models based on medical datasets, such as magnetic resonance imaging and computerized tomography in computation biomechanics. Direct conversion of graphic voxels to FE elements is a commonly used method for the generation of FE models. However, conventional voxel-based methods tend to produce models with jagged surfaces. This is a consequence of the inherent characteristics of voxel elements; such a model is unable to capture the geometries of anatomical structures satisfactorily. We have developed a robust technique for the automatic generation of voxel-based patient-specific FE models. Our approach features a novel tetrahedronization scheme that incorporates marching-cubes surface smoothing together with a smooth-distortion factor (SDF). The models conform to the actual geometries of anatomical structures of a lumbar spine segment (L3). The resultant finite element analysis (FEA) at the surfaces is more accurate compared to the use of conventional voxel-based generated FE models. In general, models produced by our method were superior compared to that obtained using the commercial software ScanFE.