Abstract
In this paper we report on a system for knowledge based interpretation of cranial MR images which has been set up within the framework of the European Community funded COVIRA project consortium [1]. The system combines an image-data-driven (bottom up) image segmentation based on fuzzy clustering with a model-driven (top down) interpretation approach which is based on fuzzy relational matching and fuzzy clique search. The application domain knowledge is represented in four knowledge sources which represent the available clinical and anatomical knowledge as well as knowledge about the (MR-) sensor and MR-specific tissue parameters. From these knowledge sources, a case model in the form of a semantic net is generated, containing knowledge relevant to the particular medical case under consideration.
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