Characterizing spatio-temporal patterns for disease discrimination in cardiac echo videos

Disease-specific understanding of echocardiographic sequences requires accurate characterization of spatio-temporal motion patterns. In this paper we present a method of automatic extraction and matching of spatio-temporal patterns from cardiac echo videos. Specifically, we extract cardiac regions (chambers and walls) using a variation of multiscale normalized cuts that combines motion estimates from deformable models with image intensity. We then derive spatio-temporal trajectories of region measurements such as wall motion, volume and thickness. The region trajectories are then matched to infer the similarities in disease labels of patients. Validation results on patient data sets collected from many hospitals are presented.