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
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.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Design, analysis and classifier evaluation for a CAD tool for breast cancer detection from digital mammograms
    Srivastava, Subodh
    Sharma, Neeraj
    Singh, Sanjay Kumar
    Srivastava, Rajeev
    INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY, 2013, 13 (03) : 270 - 300
  • [42] A brief Review on techniques used for Breast cancer detection using antennas
    Shilpa, Bagade
    Benjamin, A.
    Vignesh, N. Arun
    Kumaresham, N.
    2020 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI - 2020), 2020, : 1 - 3
  • [43] A Systematic Review on Breast Cancer Detection Using Deep Learning Techniques
    Kamakshi Rautela
    Dinesh Kumar
    Vijay Kumar
    Archives of Computational Methods in Engineering, 2022, 29 : 4599 - 4629
  • [44] A Systematic Review on Breast Cancer Detection Using Deep Learning Techniques
    Rautela, Kamakshi
    Kumar, Dinesh
    Kumar, Vijay
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2022, 29 (07) : 4599 - 4629
  • [45] EARLY DETECTION OF BREAST CANCER USING GLCM FEATURE EXTRACTION IN MAMMOGRAMS
    Kamalakannan, J.
    Babu, Rajasekhara M.
    IIOAB JOURNAL, 2016, 7 (05) : 170 - 179
  • [46] An efficient hybrid methodology for an early detection of breast cancer in digital mammograms
    Singh L.
    Alam A.
    Journal of Ambient Intelligence and Humanized Computing, 2024, 15 (1) : 337 - 360
  • [47] MMBCD: Multimodal Breast Cancer Detection from Mammograms with Clinical History
    Jain, Kshitiz
    Bansal, Aditya
    Rangarajan, Krithika
    Arora, Chetan
    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2024, PT I, 2024, 15001 : 144 - 154
  • [48] A Method for Microcalcifications Detection in Breast Mammograms
    Abbas H. Hassin Alasadi
    Ahmed Kadem Hamed Al-Saedi
    Journal of Medical Systems, 2017, 41
  • [49] A Retrospective Chart Analysis Comparing Breast Cancer Detection Rates Between Annual Versus Biennial Mammograms
    Patel, Pavan
    Sakhi, Hifza
    Kalvapudi, Devaki
    Changas, Angelo
    Sulaimanov, Mukhamed
    Gutierrez, Brian Criollo
    Umana, Idopise
    Slaton, Jake A.
    Singh, Hardeep
    JOURNAL OF CLINICAL MEDICINE RESEARCH-CANADA, 2024, 16 (12): : 608 - 624
  • [50] A Method for Microcalcifications Detection in Breast Mammograms
    Alasadi, Abbas H. Hassin
    Al-Saedi, Ahmed Kadem Hamed
    JOURNAL OF MEDICAL SYSTEMS, 2017, 41 (04)