Enhancement and Segmentation of Mammograms for Further Analysis
dc.contributor.author | Kayode, Aderonke Anthonia | |
dc.date.accessioned | 2022-03-08T11:19:27Z | |
dc.date.available | 2022-03-08T11:19:27Z | |
dc.date.issued | 2017-06 | |
dc.description | Biomedical image Processing | en_US |
dc.description.abstract | Breast cancer is the most prevalent cancer and the leading terminal disease among women worldwide. At the present time, there are no effective ways to prevent breast cancer, because its cause is not yet fully known, therefore, early detection, which can be achieved by mammography, has become the only effective way to diagnose and manage breast cancer. To diagnose breast cancer, Radiologists need to examine mammograms to locate abnormalities like masses and calcifications that indicate breast cancer. These abnormalities are very tiny in size and are obscured by the fibroglandular tissue of the breast region. The fibroglandular region of the breast is being evaluated by the Radiologist in the interpretation of mammographic images. Nevertheless, the interpretation is subjective and varies from one Radiologist to another. In this paper, mammograms acquired from the Department of Radiology, Obafemi Awolowo University Teaching Hospital Complex (OAUTHC), Ile-Ife, Nigeria were enhanced and segmented to improve and make better further analysis of the images by Radiologists. | en_US |
dc.identifier.citation | 17. Kayode AA, Odeniyi OA and Efunboade AO (2017). Enhancement and Segmentation of Mammograms for Further Analysis: International Journal of Computer Science and Information Security (IJCSIS). Vol 15 No. 6, pp 417-424. | en_US |
dc.identifier.uri | http://dspace.run.edu.ng:8080/jspui/handle/123456789/2047 | |
dc.language.iso | en | en_US |
dc.publisher | International Journal of Computer Science and Information Security (IJCSIS) | en_US |
dc.subject | Enhancement | en_US |
dc.subject | Segmentation | en_US |
dc.subject | Region of interest | en_US |
dc.subject | Breast cancer | en_US |
dc.title | Enhancement and Segmentation of Mammograms for Further Analysis | en_US |
dc.type | Article | en_US |