Understanding coronary artery movement: a knowledge-based approach

The aim of this paper is to describe a knowledge-based system that interprets three-dimensional (3D) coronary artery movement, using data from digital subtraction angiography image sequences. Dynamic information obtained from artery centerline 3D reconstruction and optical flow estimation, is classified according to experimental evidence indicating that artery displacements are quasi-homogeneous by a segment analysis. Characteristic motion features like displacement direction, perpendicular/radial components, rotation direction, curvature and torsion are qualitatively described from an image sequence using symbolic labels. These facts are then related and interpreted using anatomical-functional knowledge provided by a specialist, as well as spatial and temporal knowledge, applying spatio-temporal reasoning schemes. Facts, knowledge and reasoning rules are stated in a declarative form. Detailed examples of local and global interpretation results, using a real reconstructed angiographic biplane image sequence are presented in order to illustrate how our system suitably interprets coronary artery dynamic behavior.