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The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including those from the School of Psychological Sciences & Health - but also papers by researchers based within the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

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Fuzzy weighted-offset multi-scale edge detection for automatic echocardiographic lV boundary extraction

Sheikh Akbari, A. and Soraghan, J.J. (2002) Fuzzy weighted-offset multi-scale edge detection for automatic echocardiographic lV boundary extraction. In: IEE Seminar Medical Applications of Signal Processing, 2002-10-07 - 2002-10-07.

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Abstract

This paper describes a new Fuzzy, Weighted-Offset, Multiscale Edge Detection algorithm for cardiac left ventricular (LV) epicardial and endocardial boundary detection on short axis (SA) echocardiographic images. The proposed method uses the `centre-based' approach, previously described in S.K. Setarehdan and J.J. Soraghan, 1999, IEEE Transaction on Biomedical Engineering. Vol. 46, No. 11, 1364 - 1378. The Edge-detection stage uses a new Fuzzy Weighted Offset Multiscale Edge Detection (FWOMED) technique in order to identify a single moving point for each one of the epicardial and endocardial boundaries over the N radii in an echocardiographic frame. This technique achieves optimal edge detection through non-decimated wavelet decomposition of the original signal followed by a fuzzy based decision technique, which is applied across the scales. Finally, a uniform cubic B-spline approximation is used to define the closed LV boundaries. The performance of this technique is compared to Mallat's (S. Mallat and S. Zhong, 1992, IEEE Trans. PAMI, Vol. 14, No. 7, 710-723.) multiscale edge detection technique, for a range of test data sets comprising different synthetic noisy signals.