| dc.contributor.author | Mwadulo, Mary Walowe | |
| dc.contributor.author | Angulu, Raphael | |
| dc.contributor.author | Mutua, Stephen Makau | |
| dc.date.accessioned | 2021-10-08T11:21:57Z | |
| dc.date.available | 2021-10-08T11:21:57Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Mwadulo, M. W., Angulu, R., & Mutua, S. M. (2020). Breast Cancer Detection via Mammographic Images: A Survey. Breast cancer, 5(6), 7. | en_US |
| dc.identifier.issn | 2456-3307 | |
| dc.identifier.uri | http://repository.must.ac.ke/handle/123456789/410 | |
| dc.description.abstract | Breast cancer is a top killer disease for women globally. The long term survival rate of women can be improved through early and effective screening of breast cancer cells. Currently, a mammogram is the recommended tool for breast cancer screening since it can identify breast cancer cells several years before physical signs appear and it is cost effective. This paper analyzes mammographic detection of breast cancer by providing an explanation on development and classification of Breast Cancer, Image representation models for breast tumor, mammography technologies, a discussion on various mammographic signs of breast cancer, breast cancer feature extraction
techniques, popular breast cancer classification techniques, comparative analysis of existing mammogram breast cancer databases, and a review of mammographic breast cancer detection studies are presented. Finally, a highlight on future work is given. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | International Journal of Scientific Research in Computer Science, Engineering and Information Technology | en_US |
| dc.subject | Mammography | en_US |
| dc.subject | Feature extraction | en_US |
| dc.subject | Classification | en_US |
| dc.subject | Database | en_US |
| dc.subject | Breast Cancer | en_US |
| dc.title | Breast Cancer Detection via Mammographic Images: A Survey | en_US |
| dc.type | Article | en_US |
