Automated Segmentation of Cardiac Magnetic Resonance Images

Mikkel Bille Stegmann, Jens Chr. Nilsson, Bjørn A. Grønning

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    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.
    Original languageEnglish
    Title of host publicationProc. International Society of Magnetic Resonance In Medicine - ISMRM 2001, Glasgow, Scotland, UK
    Number of pages827
    PublisherISMRM
    Publication date2001
    Publication statusPublished - 2001
    EventProc. International Society of Magnetic Resonance In Medicine - ISMRM 2001, Glasgow, Scotland, UK - Berkeley, CA, USA
    Duration: 1 Jan 2001 → …

    Conference

    ConferenceProc. International Society of Magnetic Resonance In Medicine - ISMRM 2001, Glasgow, Scotland, UK
    CityBerkeley, CA, USA
    Period01/01/2001 → …

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