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 - 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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