• DocumentCode
    548038
  • Title

    Mass detection in mammograms using GA based PCA and Haralick features selection

  • Author

    Amroabadi, S.H. ; Ahmadzadeh, M.R. ; Hekmatnia, A.

  • Author_Institution
    Electr. & Comput. Eng. Dept., Univ. of Toronto, Toronto, ON, Canada
  • fYear
    2011
  • fDate
    17-19 May 2011
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Many existing researches utilized different types of feature extraction techniques to detect masses in ROI images. Based on our observations, inclusion of additional features beyond a certain point worsens the performance rather than enhancing it. This paper describes a hybrid method of mammogram recognition which is based on principle component analysis, Haralick features and Genetic algorithm to select the best features.
  • Keywords
    cancer; diagnostic radiography; feature extraction; genetic algorithms; mammography; medical image processing; principal component analysis; GA based PCA; Haralick feature selection; ROI images; feature extraction techniques; genetic algorithm; hybrid method; mammogram mass detection; mammogram recognition; principal component analysis; Digital mammography; Genetic algorithm; Principle Component Analysis; cooccurrence matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering (ICEE), 2011 19th Iranian Conference on
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4577-0730-8
  • Type

    conf

  • Filename
    5955928
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=548038