Abstract
The aim of this chapter is to present a graph image language techniques to the development of a syntactic semantic description of spatial visualizations of coronary artery system. The proposed linguistic description makes it possible to intelligently model the examined structure and then to advanced classification and cognitive interpretation of coronary arteries (automatically find the locations of significant stenoses and identify their morphometric diagnostic parameters). This description will be correctly formalised using ETPL(k) (Embedding Transformation-preserved Production-ordered k-Left nodes unambiguous) graph grammars, supporting the search for stenoses in the lumen of arteries forming parts of the coronary vascularisation. ETPL(k) grammars generate IE graphs (indexed edge-unambiguous) which can unambiguously represent 3D structures of heart muscle vascularisation visualised in images acquired during diagnostic examinations with the use of spiral computed tomography.
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Trzupek, M. (2012). Graph Image Language Techniques Supporting Advanced Classification and Cognitive Interpretation of CT Coronary Vessel Visualizations. In: Ogiela, M., Jain, L. (eds) Computational Intelligence Paradigms in Advanced Pattern Classification. Studies in Computational Intelligence, vol 386. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24049-2_6
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DOI: https://doi.org/10.1007/978-3-642-24049-2_6
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