CT data sets surface extraction for biomechanical modeling of long bones

In modelling applications such as custom-made: implants design is useful to have a surface representation of the anatomy of bones rather than the voxe l-based representation generated by tomography systems. A voxel-to-surface conversion process is usually done by a 2D segmentation of the images stack . However, other methods allow a direct 3D segmentation of the CT or MRI da ta set. In the present work, two of these methods, namely the Standard Marc hing Cube (SMC) and the Discretized Marching Cube (DMC) algorithms, were co mpared in terms of local accuracy when used to reconstruct the geometry of a human femur. The SMC method was found to be more accurate than the DMC me thod. The SMC method was capable of reconstructing the inner and outer geom etry of a human femur with a peak error lower than 0.9 mm and an average er ror comparable to the pixel size (0.3 mm). However, the large number of tri angles generated by the algorithm may limit its adaption in many modelling applications. The peak error of the DMC algorithm was 1.6 mm but it produce d similar to 70% less triangles than the SMC method. From the results of th is study, it may be concluded that three dimensional segmentation algorithm s are useful not only in visualisation applications but also in the creatio n of geometry models. (C) 1999 Elsevier Science Ireland Ltd. All rights res erved.