Improving visual detection of wall motion abnormality with echocardiographic image enhancing methods

Analysis of wall motion abnormality using echocardiography is an established method for detecting myocardial ischemia. We describe a hybrid approach of enhancing 2D+T echo datasets with border detection and Eulerian motion magnification to improve the visual assessment of wall motion. We implemented a local phase-based approach using the monogenic signal and its derived features, either feature asymmetry (FA) or oriented feature symmetry (OFS), to detect boundaries of the heart structure. We enhanced the 2D+T datasets using either an intensity-based or phase-based Eulerian Motion Magnification (EMM) video processing technique, and identified among eight different types of enhancements the best performing method as OFS with an accuracy of 78% versus the original B-Mode with an accuracy of 71%