Handbook of medical imaging
Ontological models as tools for image content understanding
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
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This paper presents theoretical fundamentals and application of context-free and graph languages for cognitive analysis of selected medical visualization. It shows new opportunities for applying these methods automatic understanding of semantic contents of images in intelligent medical information systems. A successful extraction of the crucial semantic content of medical image may contribute considerably to the creation of new intelligent cognitive systems, or medical computer vision systems. Thanks to the new idea of cognitive resonance between a stream of the data extracted from the image using linguistic methods, and expectations following from the language representation of the medical knowledge, it is possible to understand the subject-oriented content of the visual data. This article shows that structural techniques of soft-computing may be applied in automatic classification and machine perception based on semantic pattern content in order to determine the semantic meaning of the patterns.