Microcalcifications segmentation using three edge detection techniques

Citation

Yasiran, Siti Salmah and Jumaat, Abdul Kadir and Abdul Malek, Aminah and Hashim, Fatin Hanani and Nasrir, Nor Dhaniah and Sayed Hassan, Syarifah Nurul Azirah and Ahmad, Normah and Mahmud, Rozi (2012) Microcalcifications segmentation using three edge detection techniques. In: IEEE International Conference on Electronics Design, Systems and Applications (ICEDSA 2012), 5-6 Nov. 2012, Seri Pacific Hotel, Kuala Lumpur. (pp. 207-211).

Abstract

Edge detection has been widely used especially in medical image processing field. In this paper we are comparing Sobel, Prewitt and Laplacian of Gaussian (LoG) edge detection techniques in segmenting the boundary of microcalcifications. The edge detection must satisfy the breast phantom scoring criteria before the segmentation phase is carried out. Then, all of the edge detection techniques are implemented in the Enhanced Distance Active Contour (EDAC) model for the segmentation process. Results obtained from Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve shows that the Prewitt edge detection has the highest value of AUC, followed by the Sobel and LoG which are 0.79, 0.72 and 0.71 respectively.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Medicine and Health Science
DOI Number:	https://doi.org/10.1109/ICEDSA.2012.6507798
Publisher:	IEEE
Keywords:	Edge detection; Sobel; Prewitt; Laplacian of Gaussian; Segmentation; Mammogram
Depositing User:	Azian Edawati Zakaria
Date Deposited:	13 Jul 2015 03:46
Last Modified:	31 Oct 2016 07:10
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICEDSA.2012.6507798
URI:	http://psasir.upm.edu.my/id/eprint/39272
Statistic Details:	View Download Statistic

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