Graph-based semantic description and information extraction in analysis of 3D coronary vessels visualizations

Abstract

The work presents new possibilities for making semantic description and interpretation of some medical visualization with the use of Computational Intelligence linguistic formalisms. The methodology described in this work makes possible to find, for each considered biological 3D structure, its semantic description whose elements make reference to the medical significance of the entire structure described, while at the same time refrain from the formal differences (i.e. appearance and shape) of individual visualisations. Such methodology may be further used for attaining other goals related to computer-assisted semantic interpretation of selected elements and/or the entire 3D structure of the coronary vascular tree. The obtained semantic information allows to make a description of the structure, focused on the semantics of various heart muscle lesions. Thanks to these, the analysis conducted allows fast and automated interpretation of the semantics of various morphological changes in the coronary vascular tree. Especially it is possible to detect stenoses in the lumen of the vessels that can cause critical decrease of blood supply to extensive or especially important fragments of the heart muscle. The basis for the construction of 3D reconstructions of biological objects used in this work are visualisations obtained from helical CT scans, yet the method itself may be applied also for other methods of medical 3D images acquisition.