Automatic estimation of left ventricular dysfunction from echocardiogram videos
David Beymer, Tanveer Fathima Syeda-Mahmood, Arnon Amir, Fei Wang, Scott Adelman · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · 2009
Echocardiography is often used to diagnose cardiac diseases related to regional and valvular motion abnormalities. Due to the low resolution of the imaging modality, the choice of viewpoint and mode, and the experience of the sonographers, there is a large variance in the estimation of important diagnostic measurements such as ejection fraction. In this paper, we develop an automatic algorithm to estimate diagnostic measurements from raw echocardiogram video sequences. Specifically, we locate and track the left ventricular region over a heart cycle using active shape models. We also present efficient ventricular localization in video sequences by automatically detecting and propagating echocardiographer annotations. Results on a large database of cardiac echo videos demonstrate the use of our method for the prediction of left ventricular dysfunction.