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Automatic boundary detection of wall motion in two-dimensional echocardiography images


Dawood, Faten Abed Ali and O. K. Rahmat, Rahmita Wirza and Dimon, Mohd Zamrin and Abdullah, Lili Nurliyana and Kadiman, Suhaini (2011) Automatic boundary detection of wall motion in two-dimensional echocardiography images. Journal of Computer Science, 7 (8). pp. 1261-1266. ISSN 1549-3636; ESSN: 1552-6607


Problem statement: Medical image analysis is a particularly difficult problem because the inherent characteristics of these images, including low contrast, speckle noise, signal dropouts and complex anatomical structures. An accurate analysis of wall motion in Two-dimensional echocardiography images is "important clinical diagnosis parameter for many cardiovascular diseases". A challenge most researchers faced is how to speed up the clinical decisions and reduce human error of estimating accurately the true wall movements boundaries if can be done automatically will be a useful tool for assessing these diseases qualitatively and quantitatively. Approach: The proposed method involves three stages: First, the pre-processing stage for image contrast enhancement to reduce speckle-noise and to highlight certain features of interest (i.e., myocardial tissue). In the second stage, we applied the segmentation process using thresholding technique by considering a mean value of pixels intensity as a threshold value to distinct image features (e.g., Background and object). After thresholding implementation, the two most common mathematical morphology operators 'erosion' and 'dilation' are applied to improve the efficiency of the wall boundary detection process. Finally, Robert's operator is used as edge detector to identify the wall boundaries. Results: For accuracy measurement, the experimental results of the proposed method are compared to that obtained from medical QLab system qualitatively and quantitatively. Conclusion: The results showed that our proposed method is reliable and its performance accuracy percentages are 50% more acceptable and 42% better than QLab system results.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.3844/jcssp.2011.1261.1266
Publisher: Science Publications
Keywords: Boundary detection process; Echocardiography image; Edge detection; Mathematical morphology operators; Proposed method; Qlab system; Robert's operator; Semi-automatic algorithm; Threshold value; Wall motion
Depositing User: Nabilah Mustapa
Date Deposited: 10 Jun 2016 08:50
Last Modified: 10 Jun 2016 08:50
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/jcssp.2011.1261.1266
URI: http://psasir.upm.edu.my/id/eprint/22478
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