Abstract
In this chapter, the computational biology of cardiac cavity images is proposed. The method uses collinear and triangle equation algorithms to detect and reconstruct the boundary of the cardiac cavity. The first step involves high boost filter to enhance the high frequency component without affecting the low frequency component. Second, the morphological and thresholding operators are applied to the image to eliminate noise and convert the image into a binary image. Next, the edge detection is performed using the negative Laplacian filter and followed by region filtering. Finally, the collinear and triangle equations are used to detect and reconstruct the more precise cavity boundary. Results obtained have proved that this technique is able to perform better segmentation and detection of the boundary of cardiac cavity from echocardiographic images.
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Acknowledgements
The authors would like to thank Universiti Kebangsaan Malaysia for the funding of this research through research grant contract number UKM-GUP-TKP-08-24-080.
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Sigit, R., Mustafa, M.M., Hussain, A., Maskon, O., Nor, I.F.M. (2011). On the Use of Collinear and Triangle Equation for Automatic Segmentation and Boundary Detection of Cardiac Cavity Images. In: Arabnia, H., Tran, QN. (eds) Software Tools and Algorithms for Biological Systems. Advances in Experimental Medicine and Biology, vol 696. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7046-6_48
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DOI: https://doi.org/10.1007/978-1-4419-7046-6_48
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