Model-Based Image Segmentation: Methods and Applications

Abstract

We discuss different methods and applications of model-based segmentation of medical images. In this paper model-based segmentation is defined as the assignment of labels to pixels or voxels by matching the a priori known object model to the image data. Labels may have probabilities expressing their uncertainty. Particularly we compare optimization methods with the knowledge-based system approach.