Evaluation of semi-automated border detection algorithms for the left ventricular endocardium from magnetic resonance images

  1. Lookup NU author(s)
  2. Dr Kieren Hollingsworth
  3. Dr Andrew Sims
  4. Professor Andrew Blamire
  5. Professor Alan Murray
Author(s)Wang K, Hollingsworth K, Sims AJ, Blamire AM, Murray A
Editor(s)Murray, A.
Publication type Conference Proceedings (inc. Abstract)
Conference NameComputing in Cardiology
Conference LocationBelfast, UK
Year of Conference2010
Source Publication Date26-29 September 2010
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Left ventricular volume is an important index for a wide range of cardiovascular diseases. Magnetic resonance imaging is an accurate imaging modality for quantitative measurements of left ventricular volume. However, normally this has to be performed manually and relies on the operator's experience. We developed two semi-automated border detection algorithms to trace the left ventricular endocardial borders and calculate the volume. Comparing with the manual measurement of the left ventricular volumes, the overall bias+standard deviation was 5.9±20.4ml (algorithm 1) and 23.4±6.9ml (algorithm 2, p<;0.05) in end diastole, 6.2±4.6ml (algorithm 1, p<;0.05) and 11.1±8.9ml (algorithm 2, p<;0.05) in end systole and -0.3±22.8ml (algorithm 1) and 13.6±8.4ml (algorithm 2, p<;0.05) in stroke volume.
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