• DocumentCode
    3261880
  • Title

    A Better Classifier Based on Rough Set and Neural Network for Medical Images

  • Author

    Yun, Jiang ; Zhanhuai, Li ; Yong, Wang ; Longbo, Zhang

  • Author_Institution
    Coll. of Comput. Sci., Northwestern Polytech. Univ.
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    853
  • Lastpage
    857
  • Abstract
    Detecting tumor in mammography is a difficult task because of complexity in the image. This brings the necessity of creating automatic tools to find whether a mammography present tumor or not. In this paper we integrate neural network with reduction of rough set theory which we call the rough neural network (RNN) to classify digital mammography. The experimental results show that the RNN performs better than purely using neural network in terms of time, and it can get 92.37% classifying accuracy which is higher than 81.25% using neural network only
  • Keywords
    image classification; mammography; medical image processing; neural nets; rough set theory; tumours; digital mammography; medical image classification; rough neural network; rough set theory; tumor detection; Biomedical imaging; Breast cancer; Data mining; Educational institutions; Feature extraction; Mammography; Medical diagnostic imaging; Neoplasms; Neural networks; Recurrent neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2702-7
  • Type

    conf

  • DOI
    10.1109/ICDMW.2006.1
  • Filename
    4063745