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A novel method to use model libraries in segmentation is introduced. Using similarity measures one model from a model library is selected. This model is then used in model-based segmentation. The proposed method is simple, straightforward and fast. Various similarity measures, both voxel and edge measures, were examined. Two different segmentation methods were used for validating the functionality of the proposed procedure. Results show that a statistically significant improvement in segmentation accuracy was achieved in each study case.

Model Library for Deformable Model-Based Segmentation of 3-D Brain MR-Images