HYBRID REGISTRATION OF CORRESPONDING MAMMOGRAM IMAGES FOR AUTOMATIC DETECTION OF BREAST CANCER

被引:1
|
作者
Chiou, Yih-Chih [1 ]
Lin, Chern-Sheng [2 ]
Lin, Cheng-Yu [1 ]
机构
[1] Chung Hua Univ, Dept Mech Engn, Hsinchu, Taiwan
[2] Feng Chia Univ, Dept Automat Control Engn, Taichung, Taiwan
关键词
Mutual information; Mammogram registration; Thin-plate splines; Feature matching;
D O I
10.4015/S101623720700046X
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Mammogram registration is a critical step in automatic detection of breast cancer. Much research has been devoted to registering mammograms using either feature-matching or similarity measure. However, a few studies have been done on combining these two methods. In this research, a hybrid mammogram registration method for the early detection of breast cancer is developed by combining feature-based and intensity-based image registration techniques. Besides, internal and external features were used simultaneously during the registration to obtain a global spatial transformation. The experimental results indicates that the similarity between the two mammograms increases significantly after a proper registration using the proposed TPS-registration procedures.
引用
收藏
页码:359 / 374
页数:16
相关论文
共 50 条
  • [31] Mammogram CAD, hybrid registration and iconic analysis
    Boucher, A.
    Cloppet, F.
    Vincent, N.
    IMAGE PROCESSING: MACHINE VISION APPLICATIONS VI, 2013, 8661
  • [32] A Novel Approach for Breast Cancer Detection and Segmentation in a Mammogram
    Singh, Anuj Kumar
    Gupta, Bhupendra
    ELEVENTH INTERNATIONAL CONFERENCE ON COMMUNICATION NETWORKS, ICCN 2015/INDIA ELEVENTH INTERNATIONAL CONFERENCE ON DATA MINING AND WAREHOUSING, ICDMW 2015/NDIA ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE AND SIGNAL PROCESSING, ICISP 2015, 2015, 54 : 676 - 682
  • [33] Hybrid Feature Selection Using the Firefly Algorithm for Automatic Detection of Benign/Malignant Breast Cancer in Ultrasound Images
    Jesuharan, Dafni Rose
    Delsy, Thason Thaj Mary
    Kandasamy, Vijayakumar
    Kanagasabapathy, Pradeep Mohan Kumar
    TRAITEMENT DU SIGNAL, 2023, 40 (06) : 2671 - 2681
  • [34] An automatic detection of microcalcification in mammogram images using neuro-fuzzy classifier
    Ganvir, Neha N.
    Yadav, Dinkar Manik
    INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY, 2022, 40 (02) : 130 - 145
  • [35] Breast Cancer Detection and Classification from Mammogram Images Using Multi-model Shape Features
    Gurudas V.R.
    Shaila S.G.
    Vadivel A.
    SN Computer Science, 3 (5)
  • [36] COMBINATION OF NOISE REMOVAL AND CONTRAST ENHANCEMENT METHODS FOR THE PREPROCESSING OF MAMMOGRAM IMAGES - TOWARDS THE DETECTION OF BREAST CANCER
    Senthilkumar, B.
    Gowrishankar, R.
    Vaishnavi, M.
    Gokila, S.
    BIOSCIENCE JOURNAL, 2017, 33 (06): : 1653 - 1658
  • [37] Advancing Breast Cancer Detection: Enhancing YOLOv5 Network for Accurate Classification in Mammogram Images
    Anas, Muhammad
    Ul Haq, Ihtisham
    Husnain, Ghassan
    Jaffery, Syed Ali Faraz
    IEEE ACCESS, 2024, 12 : 16474 - 16488
  • [38] A Novel CNN-Inception-V4-Based Hybrid Approach for Classification of Breast Cancer in Mammogram Images
    Nazir, Muhammad Saquib
    Khan, Usman Ghani
    Mohiyuddin, Aqsa
    Al Reshan, Mana Saleh
    Shaikh, Asadullah
    Rizwan, Muhammad
    Davidekova, Monika
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [39] Classification of breast cancer mammogram images using convolution neural network
    Albalawi, Umar
    Manimurugan, S.
    Varatharajan, R.
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2022, 34 (13):
  • [40] Automatic Mitosis and Nuclear Atypia Detection for Breast Cancer Grading in Histopathological Images using Hybrid Machine Learning Technique
    Maheshwari N.U.
    SatheesKumaran S.
    Multimedia Tools and Applications, 2024, 83 (42) : 90105 - 90132