A novel mammogram enhancement algorithm using fuzzy logic technique

被引:0
|
作者
Guo, YH [1 ]
Huang, JH [1 ]
Tang, XL [1 ]
机构
[1] Harbin Inst Technol, Dept Comp Sci, Harbin 150006, Heilongjiang, Peoples R China
关键词
fuzzy logic; maximum entropy principle; S-function enhance;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Breast cancer is still a serious disease in many countries. Early detection is very important for diagnosis. Mammography has been one of the most reliable methods for early detection of breast cancer. However, the fuzzy nature of the mammograms and the low contrast between the breast cancer and tissue make the radiologists difficult provide accurate and effective diagnose. In this paper, an enhancement algorithm based on fuzzy logic technique is presented. In the first step, we normalize the mammograms and then fuzzify the normalized mammograms based on the maximum information entropy principle. Local information is extracted to measure the degree of enhancement, and details of mammograms can be enhanced and the noise can be suppressed. Finally, the defuzzification operation is used to transform the enhanced mammogram back to spatial domain. The experiments show that the proposed method can effectively enhance fine details of the mammogram features and reduce the affection of noise..
引用
收藏
页码:660 / 663
页数:4
相关论文
共 50 条
  • [21] Breast ultrasound image enhancement using fuzzy logic
    Guo, YH
    Cheng, HD
    Huang, JH
    Tian, JW
    Zhao, W
    Sun, LT
    Su, YX
    ULTRASOUND IN MEDICINE AND BIOLOGY, 2006, 32 (02): : 237 - 247
  • [22] Breast Ultrasound Images Enhancement Using Fuzzy Logic
    Wang, Yu-juan
    Lu, Shu-xi
    FIRST INTERNATIONAL WORKSHOP ON DATABASE TECHNOLOGY AND APPLICATIONS, PROCEEDINGS, 2009, : 658 - 661
  • [23] Enhancement of Visual Quality of an Image Using Fuzzy Logic
    Aarthi, T.
    Sowmiya, E.
    Sairam, N.
    2014 IEEE 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL (ISCO), 2014, : 240 - 242
  • [24] Type 2 Fuzzy Logic for Mammogram Breast Tissue Classification
    Baharuddin, Wan Noor Aziezan
    Abdullah, Siti Norul Huda Sheikh
    Sahran, Shahnorbanun
    Qasem, Ashwaq
    bin Abdullah, Azizi
    Iqbal, Rizuana
    Ismail, Fuad
    2016 INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS AND COMPUTER SYSTEMS (CIICS), 2016,
  • [25] Detection of Suspicious Lesions in Mammogram using Fuzzy C-Means Algorithm
    Kumar, Mukesh
    Thakkar, V. M.
    Bhatt, Upendra
    Soliyal, Neema
    2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2016, : 1553 - 1557
  • [26] A new adjusting technique for PID type fuzzy logic controller using PSOSCALF optimization algorithm
    Bejarbaneh, Elham Yazdani
    Bagheri, Ahmad
    Bejarbaneh, Behnam Yazdani
    Buyamin, Salinda
    Chegini, Saeed Nezamivand
    APPLIED SOFT COMPUTING, 2019, 85
  • [27] Image Contrast Enhancement using Fuzzy Technique
    Reshmalakshmi, C.
    Sasikumar, M.
    PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON CIRCUITS, POWER AND COMPUTING TECHNOLOGIES (ICCPCT 2013), 2013, : 861 - 865
  • [28] Edge enhancement using fuzzy reasoning technique
    Chen, Q
    Zheng, NN
    2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 1010 - 1012
  • [29] Image contrast enhancement using fuzzy technique
    Reshmalakshmi, C.
    Sasikumar, M.
    Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2013, 2013, : 861 - 865
  • [30] A Novel Technique for Mammogram Mass Segmentation Using Fractal Adaptive Thresholding
    Shanmugavadivu, P.
    Sivakumar, V.
    8TH INTERNATIONAL CONFERENCE ON ROBOTIC, VISION, SIGNAL PROCESSING & POWER APPLICATIONS: INNOVATION EXCELLENCE TOWARDS HUMANISTIC TECHNOLOGY, 2014, 291 : 213 - 220