Segmentation of the myocardium from myocardial contrast echocardiography

John E. Pickard, Rob L. Janiczek, Scott T. Acton, Jiri Sklenar, John A. Hossack, Sanjiv Kaul

    Research output: Contribution to journalConference articlepeer-review

    3 Scopus citations


    Myocardial contrast echocardiography (MCE) is a promising new technique that allows quantification of myocardium perfusion and therefore accurate diagnosis of coronary artery disease. MCE data, however, have previously required tedious and time-consuming off-line manual image processing. This paper presents results that demonstrate success of an automatic segmentation approach utilizing active shape models. A shape model was created from a training set of eleven manually drawn contours, which was then applied to twenty-two MCE images. Standard success metrics show that error from this automatic method is comparable to error found among manually drawn contours. Additionally, a more robust calculation of the key blood flow parameters was developed which can accommodate error in the segmentation, verified by high correlation between manually and automatically derived parameters.

    Original languageEnglish (US)
    Pages (from-to)1616-1619
    Number of pages4
    JournalConference Record - Asilomar Conference on Signals, Systems and Computers
    StatePublished - Dec 1 2004
    EventConference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
    Duration: Nov 7 2004Nov 10 2004

    ASJC Scopus subject areas

    • Signal Processing
    • Computer Networks and Communications


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