• DocumentCode
    2819142
  • Title

    A fuzzy inference system combined with wavelet transform for breast mass classification

  • Author

    Görgel, Pelin ; Sertbas, Ahmet ; Ucan, Osman N.

  • Author_Institution
    Comput. Eng. Dept., Univ. of Istanbul, Istanbul, Turkey
  • fYear
    2012
  • fDate
    3-4 July 2012
  • Firstpage
    644
  • Lastpage
    647
  • Abstract
    This paper proposes a combination of the Fast Wavelet Transform (FWT) and Adaptive Neuro-fuzzy Inference System (ANFIS) methods. The goal is classification of breast masses as benign or malignant by applying this method consecutively to the extracted features of the Region of Interests (ROIs). This study is developed to decrease the number of the missing cancerous regions or unnecessary biopsies. The neuro-fuzzy subtractive clustering classification method achieved a classification accuracy of 85% without using FWT multi-resolution analysis and 92% with FWT. The satisfying results demonstrate that the developed system could help the radiologists for a true diagnosis.
  • Keywords
    cancer; feature extraction; fuzzy neural nets; fuzzy reasoning; gynaecology; image classification; medical image processing; pattern clustering; radiology; wavelet transforms; ANFIS; FWT; ROI; adaptive neuro-fuzzy inference system methods; biopsies; breast mass classification; cancerous regions; extracted features; fast wavelet transform; neuro-fuzzy subtractive clustering classification method; radiologists; region of interests; Cancer; Computers; Feature extraction; Shape; Training; Wavelet transforms; ANFIS; Breast cancer; fast wavelet transform; mass classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications and Signal Processing (TSP), 2012 35th International Conference on
  • Conference_Location
    Prague
  • Print_ISBN
    978-1-4673-1117-5
  • Type

    conf

  • DOI
    10.1109/TSP.2012.6256376
  • Filename
    6256376