@CONFERENCE\{IMM2001-0119,
    author       = "M. B. Stegmann and J. C. Nilsson and B. A. Gr{\o}nning",
    title        = "Automated Segmentation of Cardiac Magnetic Resonance Images",
    year         = "2001",
    month        = "apr",
    pages        = "827",
    booktitle    = "Proc. International Society of Magnetic Resonance In Medicine - {ISMRM} 2001, Glasgow, Scotland, {UK}",
    volume       = "2",
    series       = "",
    editor       = "",
    publisher    = "ISMRM",
    organization = "",
    address      = "Berkeley, {CA,} {USA}",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/119-full.html",
    abstract     = "Magnetic resonance imaging (MRI) has been shown to be an accurate and precise technique to assess cardiac volumes and function in a non-invasive manner and is generally considered to be the current gold-standard for cardiac imaging [1]. Measurement of ventricular volumes, muscle mass and function is based on determination of the left-ventricular endocardial and epicardial borders. Since manual border detection is laborious, automated segmentation is highly desirable as a fast, objective and reproducible alternative. Automated segmentation will thus enhance comparability between and within cardiac studies and increase accuracy by allowing acquisition of thinner {MRI-}slices. This abstract demonstrates that statistical models of shape and appearance, namely the deformable models: Active Appearance Models, can successfully segment cardiac MRIs."
}