Breast Cancer Detection : A Review On Mammograms Analysis Techniques

被引:0
|
作者
Hela, Boulehmi [1 ]
Hela, Mahersia [1 ]
Kamel, Hamrouni [1 ]
Sana, Boussetta
Najla, Mnif
机构
[1] Univ Tunis El Manar, Ecole Natl Ingn Tunis, LR SITI Signal Image & Technol Informat, Tunis, Tunisia
来源
2013 10TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD) | 2013年
关键词
breast cancer; early detection; breast density; mammograms analysis; COMPUTER-AIDED DIAGNOSIS; CLUSTERED MICROCALCIFICATIONS; DIGITAL MAMMOGRAMS; PARENCHYMAL PATTERNS; AUTOMATED DETECTION; CIRCUMSCRIBED MASSES; FEATURE ENHANCEMENT; NEURAL-NETWORKS; SEGMENTATION; CLASSIFICATION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Breast cancer is the most common cancer among women over 40 years. Studies have shown that early detection and appropriate treatment of breast cancer significantly increase the chances of survival. They have also shown that early detection of small lesions boosts prognosis and leads to a significant reduction in mortality. Mammography is in this case the best diagnostic technique for screening. However, the interpretation of mammograms is not easy because of small differences in densities of different tissues within the image. This is especially true for dense breasts. This paper is a survey of the automatic early detection of breast cancer by analyzing mammographic images. This analysis could provide radiologists a better understanding of stereotypes and provides, if it is detected at an early stage, a better prognosis inducing a significant decrease in mortality.
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页数:6
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