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

Lookup NU author(s): Dr Kieren Hollingsworth, Dr Andrew SimsORCiD, Professor Andrew BlamireORCiD, Emeritus Professor Alan MurrayORCiD


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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.

Publication metadata

Author(s): Wang K, Hollingsworth K, Sims AJ, Blamire AM, Murray A

Editor(s): Murray, A.

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computing in Cardiology

Year of Conference: 2010

Pages: 809-812

ISSN: 0276-6547

Publisher: IEEE


Library holdings: Search Newcastle University Library for this item

ISBN: 9781424473182