Title :
Automatic detection of left ventricular aneurysms in echocardiograms
Author :
Mahmood, R. ; Syeda-Mahmood, T.
Author_Institution :
Monta Vista High Sch., Cupertino, CA, USA
Abstract :
Left ventricular cardiac aneurysms are bulgings in the myocardium muscle of the left ventricle. These irregular distortions of the left ventricular shape from its normal bullet-like appearance, are often due to result of myocardial infarction and can be fatal. In this paper we address, for the first time, the automatic detection of left ventricular (LV) cardiac aneurysms from 4-chamber views in echocardiograms. For this, we first detect the left ventricle in the echocardiogram image as the lumen region closest to the apex of the heart. The apex itself is estimated from the bounding lines of the viewing sector in an echocardiogram. The boundary of the LV is then analyzed to extract key curvature-based features for discrimination using a support vector machine with radial basis function kernels. Results of testing on a large echocardiogram video collection indicate that robust detection of left ventricle coupled with curvature features is sufficient to reliably separate LV aneurysms from normal left ventricular shapes.
Keywords :
diseases; echocardiography; feature extraction; medical image processing; muscle; radial basis function networks; support vector machines; automatic left ventricular cardiac aneurysm detection; curvature-based feature extraction; echocardiogram image; echocardiogram video collection; heart apex; lumen region; myocardium muscle; radial basis function kernels; support vector machine; Active shape model; Aneurysm; Echocardiography; Feature extraction; Heart; Robustness; Shape; LV detection; cardiac aneurysms; computer-aided diagnosis; curvature feature;
Conference_Titel :
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location :
New York, NY
DOI :
10.1109/ISBI.2015.7164115