• DocumentCode
    3529193
  • Title

    Texture analysis techniques for the classification of microcalcifications in digitised mammograms

  • Author

    Kramer, Dani ; Aghdasi, Farzin

  • Author_Institution
    Dept. of Electr. Eng., Univ. of the Witwatersrand, Johannesburg, South Africa
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    395
  • Abstract
    We present various image texture analysis techniques for the classification of microcalcifications in digitised mammograms. Three categories of image texture features are extracted from the microcalcifications. The set of features based on a combined statistical and multiresolution approach to texture analysis gave the best results. Both a k-nn classifier and an artificial neural network are used for classification
  • Keywords
    cancer; feature extraction; feedforward neural nets; image classification; image resolution; image texture; mammography; medical image processing; statistical analysis; artificial neural network; digitised mammograms; features; image texture analysis techniques; k-nn classifier; microcalcification classification; multiresolution approach; statistical approach; Biopsy; Breast cancer; Diagnostic radiography; Feature extraction; Image segmentation; Image texture; Image texture analysis; Lesions; Statistical analysis; Tumors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Africon, 1999 IEEE
  • Conference_Location
    Cape Town
  • Print_ISBN
    0-7803-5546-6
  • Type

    conf

  • DOI
    10.1109/AFRCON.1999.820877
  • Filename
    820877