Objective Computational simulation technology has become an indispensable tool for researchers across the biomechanics discipline. Crucial to the effectiveness of such a tool is its ability to efficiently simulate patient-specific problems. This paper will present a unique and exceptionally efficient approach that converts 3D digital images (provided typically by CT, Ultrasound or MRI scanners)directly into highly accurate computational models. Method The majority of approaches adopted have involved generating a surface model (either in a discretized or continuous format) from the scan data, which is then exported to a commercial mesher-a process which is time consuming, not very robust and virtually intractable for the complex topologies typical of image data. A more direct approach' is to combine the geometric detection and mesh creation stages in one process. This approach involves identifying volumes of interest (segmentation of 3D image) and then directly generating the volumetric mesh based on an orthotropic grid intersected by interfaces defining the boundaries. This methodology is used that generates 3D hexahedral or tetrahedral elements throughout the volume of the domain, thus creating the mesh directly. Results Treating the problem using an image-based meshing approach is remarkably straightforward, robust, accurate and efficient. Indeed meshes can be generated automatically which is of image-based accuracy with domain boundaries of the finite element model lying exactly on the iso-surfaces thereby taking into account partial volume effects and providing sub-voxel accuracy. Conclusion Meshing from image data presents a number of challenges but also unique opportunities so that a conceptually different approach can provide, in many instances, better results thantraditional approaches. The ease and accuracy with which models can be generated opens up a wide range of previously difficult or intractable problems to numerical analysis, including blood flow, and patient-specific implant design.