Shape Constrained Deformable Models for 3D Medical Image Segmentation

Abstract

To improve the robustness of segmentation methods, more and more methods use prior knowledge. We present an approach which embeds an active shape model into an elastically deformable surface model, and combines the advantages of both approaches. The shape model constrains the flexibility of the surface mesh representing the deformable model and maintains an optimal distribution of mesh vertices. A specific external energy which attracts the deformable model to locally detected surfaces, reduces the danger that the mesh is trapped by false object boundaries. Examples are shown, and furthermore a validation study for the segmentation of vertebrae in CT images is presented. With the exception of a few problematic areas, the algorithm leads reliably to a very good overall segmentation.

Acknowledgments

We thank P rof. Dr. W. P. Th. M. Mali, P rof. Dr. B. C. Eikelboom and Dr. J. D. Blankensteijn (University Hospital Utrecht) for providing the CT images with the vertebrae and Dr. J. Richolt, Dr. J. Kordelle and Brigham & Women’s Hospital for the femur data. The algorithm was implemented on an experimental version of the EasyVision workstation from Philips Medical Systems.