Publication: Exploring graph cut technique for mammography images
| datacite.subject.fos | oecd::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering | |
| dc.contributor.author | Ding, Nik Siong | |
| dc.date.accessioned | 2024-07-24T01:02:29Z | |
| dc.date.available | 2024-07-24T01:02:29Z | |
| dc.date.issued | 2009-04-01 | |
| dc.description.abstract | Breast cancer is one of the most common diseases among woman nowadays. However, the presence of medical imaging tools such as mammography enables diagnosis of breast cancer to be conducted at beginning stage of breast cancer development. Mammogram is the image produced by mammography process. The presence of abnormal structures in mammograms will indicate that the woman is having a breast cancer. In this study, a new algorithm called graph cut was explored to evaluate its efficiency to detect the presence of abnormal structures in mammograms. Although graph cut technique is new but it has generated a lot interest among the researchers in the computer vision community. The primary reason for this rising popularity has been the successes of efficient graph cut algorithm in solving many low level vision problems such as image segmentation, object reconstruction, image restoration and disparity estimation. Masses and mircocalcifications are two most common abnormal structures in mammograms. In this study, a specific mammogram segmentation algorithm was developed based on the graph cut technique. This mammogram segmentation algorithm was used to test efficiency of the graph cut technique to segment the abnormal structures out of mammograms. The success rates of detecting these abnormal structures are high. For masses, graph cut technique able to detect the mass structures in all mammograms used to test this technique. Meanwhile, for microcalcifications, graph cut technique only can detect the microcalcification structures in mammograms which show low density breast. These segmentation results proved that graph cut technique is suitable to be used to detect the presence of abnormal structures in mammograms. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/19830 | |
| dc.language.iso | en | |
| dc.title | Exploring graph cut technique for mammography images | |
| dc.type | Resource Types::text::report | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |