• DocumentCode
    497818
  • Title

    Mammogram tumor classification using multimodal features and Genetic Algorithm

  • Author

    Suganthi, M. ; Madheswaran, M.

  • Author_Institution
    Dept. of Electron. & Commun. Eng., Muthayammal Eng. Coll., Rasipuram, India
  • fYear
    2009
  • fDate
    4-6 June 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper proposes a computer aided decision support system for an automated diagnosis and classification of breast tumor using mammogram. The proposed method differentiates two breast diseases namely benign masses and malignant tumors. From the preprocessed mammogram image, texture and shape features are extracted. The optimal features can be extracted by using a feature selection scheme based on the multi objectives genetic algorithm (MOGA).The performance of the proposed method is compared with the previous methods in terms of classification accuracy, training and testing time. Simulation results show that, this approach is an efficient, easy to use and can achieve high sensitivity.
  • Keywords
    genetic algorithms; image texture; mammography; medical diagnostic computing; medical image processing; tumours; automated diagnosis; benign masses; breast diseases; breast tumor; computer aided decision support system; image texture; malignant tumors; mammogram tumor classification; multimodal features; multiobjectives genetic algorithm; Benign tumors; Breast neoplasms; Breast tumors; Decision support systems; Diseases; Feature extraction; Genetic algorithms; Malignant tumors; Shape; Testing; MOGA Classification; Mammogram; Shape features; Texture features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation, Communication and Energy Conservation, 2009. INCACEC 2009. 2009 International Conference on
  • Conference_Location
    Perundurai, Tamilnadu
  • Print_ISBN
    978-1-4244-4789-3
  • Type

    conf

  • Filename
    5204384