Abstract
In this paper a novel and robust automatic LV segmentation by measuring the properties of each connected components in the echocardiogram images and a cardiac abnormality detection method based on ejection fraction is proposed. Starting from echocardiogram videos of normal and abnormal hearts, the left ventricle is first segmented using connected component labeling and from the segmented LV region the proposed algorithm is used to calculate the left ventricle diameter. The diameter derived is used to calculate the various LV parameters. In each heart beat or cardiac cycle, the volumetric fraction of blood pumped out of the left ventricle (LV) and the ejection fraction (EF) were calculated based on which the cardiac abnormality is decided. The proposed method gave an accuracy of 93.3% and it can be used as an effective tool to segment left ventricle boundary and for classifying the heart as either normal or abnormal.
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Balaji, G.N., Subashini, T.S. (2013). Detection of Cardiac Abnormality from Measures Calculated from Segmented Left Ventricle in Ultrasound Videos. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_26
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DOI: https://doi.org/10.1007/978-3-319-03844-5_26
Publisher Name: Springer, Cham
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