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Hana Najwa Omar Rashid
Universiti Malaysia Pahang

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Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach Mahfuzah Mustafa; Hana Najwa Omar Rashid; Nor Rul Hasma Abdullah; Rosdiyana Samad; Dwi Pebrianti
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 3: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i3.pp577-583

Abstract

Breast cancer is one of the most common diseases diagnosed among female cancer patients. Early detection of breast cancer is needed to reduce the risk of fatality of this disease as no cure has been found yet for this illness. This research is conducted to improve the Gradient Vector Flow (GVF) Snake Active Contour segmentation technique in mammography segmentation. Segmentation of the mammogram image is done to segment lesions existence using Chan-Vese Active Contour and Localized Active Contour. Besides that, the effectiveness of these both methods are then compared and chosen to be the best method. Digital Database of Screening Mammograms (DDSM) is used for the purpose of screening. First, the images undergo pre-processing process using the Gaussian Low Pass Filter to remove unwanted noise. After that, contrast enhancement applied to the images. Segmentation of mammograms is then conducted by using Chan-Vese Active Contour and Localized Active Contour method. The result shows that Chan-Vese technique outperforms Localized Active Contour with 90% accuracy.
Co-Authors Dwi Pebrianti Mahfuzah Mustafa Nor Rul Hasma Abdullah Rosdiyana Samad