Intelligent image content semantic description for cardiac 3D visualisations

In these days of the rapid development of diagnostic equipment with increasingly sophisticated technology it is necessary to put more emphasis on implementing processes for the computer support of medical diagnostics, which are more and more often used to automate diagnostic procedures carried out in healthcare. Current research shows that a significant part of diagnostic imaging, including e.g. of coronary arteries, is still difficult to automatically assess using computer analysis techniques aimed at extracting information having semantic meaning. This mainly applies to images that show many structures simultaneously, as well as 3D images. In this context, this publication presents new capabilities to formulate semantic descriptions of 3D structures of coronary vascularisation using graph formalisms. The proposed syntactic semantic description makes it possible to intelligently model the examined structure and then to automatically find the locations of significant stenoses in coronary arteries and identify their morphometric diagnostic parameters. In this research, images originating from diagnostic examinations with 64-slice spiral computed tomography were used.