Statistical models of shape are a promising approach for robust and automatic segmentation of medical image
data. This work describes the construction of a statistical shape model of the pelvic bone. An interactive
approach is proposed for solving the correspondence problem which is able to handle shapes of arbitrary topology,
suitable for the genus 3 surface of the pelvic bone. Moreover it allows to specify corresponding anatomical features
as boundary constraints to the matching process. The model's capability for segmentation was tested on a set of
23 CT data sets. Quantitative results will be presented, showing that the model is well suited for segmentation
purposes.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.