Our task is to segment bones from 3D CT and MRI images. The main application is creation of 3D mesh models for finite element modeling. These surface and volume vector models can be used for further biomechanical processing and analysis. We selected a novel fast level set method because of its high computational efficiency, while preserving all advantages of traditional level set methods. Unlike in traditional level set methods, we are not solving partial differential equations (PDEs). Instead, the contours are represeted by two sets of points, corresponding to the inner and outer edge of the object boundary. We have extended the original implementation in 3D, where the speed advantage over classical level set segmentation are even more pronounced. We can segment a CT image of 512×512×125 in less than 20s by this method. It is approximately two orders of magnitude faster than standard narrow band algorithms. Our experiments with real 3D CT and MRI images presented in this paper showed high ability of the fast level set algorithm to solve complex segmentation problems.