Automated Segmentation of Cardiac Magnetic Resonance Images |
| | 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. | | Type | Conference paper [Abstract] | | Conference | Proc. International Society of Magnetic Resonance In Medicine - ISMRM 2001, Glasgow, Scotland, UK | | Year | 2001 Month April Vol. 2 pp. 827 | | Publisher | ISMRM | | Address | Berkeley, CA, USA | | Electronic version(s) | [pdf] | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
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