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Segmentation of CT images using the watershed transformation on graphs with a-priori tissue models

The combination of the watershed transformation on graphs with a tissue classification is presented. The watershed transformation on graphs results in hierarchical segmentation volumes that differ in region number and size. If an anatomical object corresponds to a region in a segmentation volume it has to be selected, since the region would be merged with the most similar neighbor region in the following volume. Such an object selection can be done using object descriptions. A possible approach is presented in this paper.