• DocumentCode
    3243812
  • Title

    Automatic detection of left ventricular aneurysms in echocardiograms

  • Author

    Mahmood, R. ; Syeda-Mahmood, T.

  • Author_Institution
    Monta Vista High Sch., Cupertino, CA, USA
  • fYear
    2015
  • fDate
    16-19 April 2015
  • Firstpage
    1308
  • Lastpage
    1311
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
  • Conference_Location
    New York, NY
  • Type

    conf

  • DOI
    10.1109/ISBI.2015.7164115
  • Filename
    7164115