• DocumentCode
    547712
  • Title

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

  • Author

    Amroabadi, SayedMasoud Hashemi ; Ahmadzadeh, Mohammad Reza ; Hekmatnia, Ali

  • Author_Institution
    Electrical and Computer Eng. Dept. University of Toronto, Toronto, Canada
  • fYear
    2011
  • fDate
    17-19 May 2011
  • Firstpage
    1
  • Lastpage
    4
  • 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
    Algorithm design and analysis; Classification algorithms; Feature extraction; Genetic algorithms; Lesions; Principal component analysis; Support vector machine classification; Digital mammography; Genetic algorithm; co-occurrence matrices; component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering (ICEE), 2011 19th Iranian Conference on
  • Conference_Location
    Tehran, Iran
  • Print_ISBN
    978-1-4577-0730-8
  • Electronic_ISBN
    978-964-463-428-4
  • Type

    conf

  • Filename
    5955601
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=547712