Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach
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) Snak...
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Institute of Advanced Engineering and Science
2017
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ump-180932018-01-15T06:53:07Z http://umpir.ump.edu.my/id/eprint/18093/ Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach Mahfuzah, Mustafa Hana Najwa, Omar Rashid Nor Rul Hasma, Abdullah Rosdiyana, Samad Pebrianti, Dwi TK Electrical engineering. Electronics Nuclear engineering 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. Institute of Advanced Engineering and Science 2017 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/18093/1/Mammography%20Image%20Segmentation-%20Chan-Vese%20Active%20Contour%20and%20Localised%20Active%20Contour%20Approach.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/18093/7/Mammography%20Image%20Segmentation-%20Chan-Vese%20Active%20Contour%20and%20Localised%20Active%20Contour%20Approach%201.pdf Mahfuzah, Mustafa and Hana Najwa, Omar Rashid and Nor Rul Hasma, Abdullah and Rosdiyana, Samad and Pebrianti, Dwi (2017) Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach. Indonesian Journal of Electrical Engineering and Computer Science, 5 (3). pp. 577-588. ISSN 2502-4752 http://iaescore.com/journals/index.php/IJEECS/article/view/6508 DOI: 10.11591/ijeecs.v5.i3.pp577-583 |
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TK Electrical engineering. Electronics Nuclear engineering |
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TK Electrical engineering. Electronics Nuclear engineering Mahfuzah, Mustafa Hana Najwa, Omar Rashid Nor Rul Hasma, Abdullah Rosdiyana, Samad Pebrianti, Dwi Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach |
description |
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. |
format |
Article |
author |
Mahfuzah, Mustafa Hana Najwa, Omar Rashid Nor Rul Hasma, Abdullah Rosdiyana, Samad Pebrianti, Dwi |
author_facet |
Mahfuzah, Mustafa Hana Najwa, Omar Rashid Nor Rul Hasma, Abdullah Rosdiyana, Samad Pebrianti, Dwi |
author_sort |
Mahfuzah, Mustafa |
title |
Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach |
title_short |
Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach |
title_full |
Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach |
title_fullStr |
Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach |
title_full_unstemmed |
Mammography Image Segmentation: Chan-Vese Active Contour and Localised Active Contour Approach |
title_sort |
mammography image segmentation: chan-vese active contour and localised active contour approach |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2017 |
url |
http://umpir.ump.edu.my/id/eprint/18093/ http://umpir.ump.edu.my/id/eprint/18093/ http://umpir.ump.edu.my/id/eprint/18093/ http://umpir.ump.edu.my/id/eprint/18093/1/Mammography%20Image%20Segmentation-%20Chan-Vese%20Active%20Contour%20and%20Localised%20Active%20Contour%20Approach.pdf http://umpir.ump.edu.my/id/eprint/18093/7/Mammography%20Image%20Segmentation-%20Chan-Vese%20Active%20Contour%20and%20Localised%20Active%20Contour%20Approach%201.pdf |
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2023-09-18T22:25:25Z |
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2023-09-18T22:25:25Z |
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1777415933753556992 |