Mammographic Images Enhancement and Denoising for Breast Cancer Detection Using Dyadic Wavelet Processing

2008 ◽  
Vol 57 (7) ◽  
pp. 1422-1430 ◽  
Author(s):  
A. Mencattini ◽  
M. Salmeri ◽  
R. Lojacono ◽  
M. Frigerio ◽  
F. Caselli
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Breast Cancer Detection ◽  
Mammographic Images ◽  
Dyadic Wavelet

scholarly journals Breast Cancer Detection via Mammographic Images : A Survey

2020 ◽  
pp. 173-195
Author(s):  
Mary Walowe Mwadulo ◽  
Raphael Angulu ◽  
Stephen Makau Mutua
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cancer Detection ◽  
Breast Cancer Cells ◽  
Cost Effective ◽  
Breast Cancer Detection ◽  
Term Survival ◽  
Mammographic Images ◽  
Cancer Breast ◽  
Future Work

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.

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