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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.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
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influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
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