Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on Mammograms Using Graph Cuts
Breast cancer mostly arises from the glandular (dense) region of the breast. Consequently, breast density has been found to be a strong indicator for breast cancer risk.Therefore, there is a need to develop a systemwhich can segment or classify dense breast areas. In a dense breast, the sensitivit...
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Online Access: | http://eprints.usm.my/38478/1/Computer_Aided_Detection_of_Breast_Density_and_Mass%2C_and_Visualization_of_Other_Breast.pdf http://eprints.usm.my/38478/ http://dx.doi.org/10.1155/2013/205384 |
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my.usm.eprints.38478 http://eprints.usm.my/38478/ Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on Mammograms Using Graph Cuts Saidin, Nafiza Mat Sakim, Harsa Amylia Ngah, Umi Kalthum Lutfi Shuaib, Ibrahim RK1-715 Dentistry TK1-9971 Electrical engineering. Electronics. Nuclear engineering Breast cancer mostly arises from the glandular (dense) region of the breast. Consequently, breast density has been found to be a strong indicator for breast cancer risk.Therefore, there is a need to develop a systemwhich can segment or classify dense breast areas. In a dense breast, the sensitivity of mammography for the early detection of breast cancer is reduced. It is difficult to detect a mass in a breast that is dense.Therefore, a computerized method to separate the existence of a mass from the glandular tissues becomes an important task.Moreover, if the segmentation results provide more precise demarcation enabling the visualization of the breast anatomical regions, it could also assist in the detection of architectural distortion or asymmetry. This study attempts to segment the dense areas of the breast and the existence of a mass and to visualize other breast regions (skin-air interface, uncompressed fat, compressed fat, and glandular) in a system.The graph cuts (GC) segmentation technique is proposed. Multiselection of seed labels has been chosen to provide the hard constraint for segmentation of the different parts.The results are promising. A strong correlation ( Hindawi Publishing Corporation 2013 Article PeerReviewed application/pdf en http://eprints.usm.my/38478/1/Computer_Aided_Detection_of_Breast_Density_and_Mass%2C_and_Visualization_of_Other_Breast.pdf Saidin, Nafiza and Mat Sakim, Harsa Amylia and Ngah, Umi Kalthum and Lutfi Shuaib, Ibrahim (2013) Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on Mammograms Using Graph Cuts. Computational and Mathematical Methods in Medicine, 2013 (205384). pp. 1-13. ISSN 1748-670X http://dx.doi.org/10.1155/2013/205384 |
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RK1-715 Dentistry TK1-9971 Electrical engineering. Electronics. Nuclear engineering Saidin, Nafiza Mat Sakim, Harsa Amylia Ngah, Umi Kalthum Lutfi Shuaib, Ibrahim Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on Mammograms Using Graph Cuts |
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Breast cancer mostly arises from the glandular (dense) region of the breast. Consequently, breast density has been found to be a
strong indicator for breast cancer risk.Therefore, there is a need to develop a systemwhich can segment or classify dense breast areas.
In a dense breast, the sensitivity of mammography for the early detection of breast cancer is reduced. It is difficult to detect a mass
in a breast that is dense.Therefore, a computerized method to separate the existence of a mass from the glandular tissues becomes
an important task.Moreover, if the segmentation results provide more precise demarcation enabling the visualization of the breast
anatomical regions, it could also assist in the detection of architectural distortion or asymmetry. This study attempts to segment
the dense areas of the breast and the existence of a mass and to visualize other breast regions (skin-air interface, uncompressed
fat, compressed fat, and glandular) in a system.The graph cuts (GC) segmentation technique is proposed. Multiselection of seed
labels has been chosen to provide the hard constraint for segmentation of the different parts.The results are promising. A strong
correlation ( |
format |
Article |
author |
Saidin, Nafiza Mat Sakim, Harsa Amylia Ngah, Umi Kalthum Lutfi Shuaib, Ibrahim |
author_facet |
Saidin, Nafiza Mat Sakim, Harsa Amylia Ngah, Umi Kalthum Lutfi Shuaib, Ibrahim |
author_sort |
Saidin, Nafiza |
title |
Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on
Mammograms Using Graph Cuts |
title_short |
Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on
Mammograms Using Graph Cuts |
title_full |
Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on
Mammograms Using Graph Cuts |
title_fullStr |
Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on
Mammograms Using Graph Cuts |
title_full_unstemmed |
Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on
Mammograms Using Graph Cuts |
title_sort |
computer aided detection of breast density and mass, and visualization of other breast anatomical regions on
mammograms using graph cuts |
publisher |
Hindawi Publishing Corporation |
publishDate |
2013 |
url |
http://eprints.usm.my/38478/1/Computer_Aided_Detection_of_Breast_Density_and_Mass%2C_and_Visualization_of_Other_Breast.pdf http://eprints.usm.my/38478/ http://dx.doi.org/10.1155/2013/205384 |
_version_ |
1643709369305530368 |
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13.18916 |