• DocumentCode
    2383771
  • Title

    Improved local binary patterns for classification of masses using mammography

  • Author

    Liu, Jun ; Liu, Xiaoming ; Chen, Jianxun ; Tang, J.

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2011
  • fDate
    9-12 Oct. 2011
  • Firstpage
    2692
  • Lastpage
    2695
  • Abstract
    In this paper, we investigate mass classification using an improved local binary pattern operator. In the proposed classification algorithm, the improved local binary pattern operator is used to extract the features of masses and is used to determine whether the mass is benign or malignant. For classifier, support vector machine is adopted. 309 images from the DDSM database were used and the experimental results show the effectiveness of the proposed algorithm.
  • Keywords
    feature extraction; image classification; mammography; medical image processing; support vector machines; DDSM database; feature extraction; local binary pattern operator; mammography; mass classification; support vector machine; Breast cancer; Cancer detection; Classification algorithms; Feature extraction; Support vector machines; Training; Mass classification; local binary pattern operator; median; support vector; texture analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4577-0652-3
  • Type

    conf

  • DOI
    10.1109/ICSMC.2011.6084079
  • Filename
    6084079