Hierarchical segmentation of thin structures in volumetric medical images

Abstract

We introduce a new method for segmentation of 3D medical data based on geometric variational principles. A minimal variance criterion is coupled with a geometric edge alignment measure and the geodesic active surface model. An efficient numerical scheme is proposed. In order to simultaneously detect a number of different objects in the image, a hierarchal method is presented. Finally, our method is compared with the multi-level set approach for segmentation of medical images.