With the recent introduction of combined Magnetic Resonance Imaging (MRI) / Positron Emission Tomography (PET) systems, the generation of attenuation maps for PET based on MR images gained substantial attention. One approach for this problem is the segmentation of structures on the MR images with subsequent filling of the segments with respective attenuation values. Structures of particular interest for the segmentation are the pelvis bones, since those are among the most heavily absorbing structures for many applications, and they can serve at the same time as valuable landmarks for further structure identification. In this work the model-based segmentation of the pelvis bones on gradient-echo MR images is investigated. A processing chain for the detection and segmentation of the pelvic bones is introduced, and the results are evaluated using CT-generated "ground truth" data. The results indicate that a model based segmentation of the pelvis bone is feasible with moderate requirements to the pre- and postprocessing steps of the segmentation.