• DocumentCode
    3130899
  • Title

    Textural Feature Analysis for Ultrasound Breast Tumor Images

  • Author

    Chen, Qiuxia ; Liu, Qi

  • Author_Institution
    Dept. of Med. Inf. Eng., Sichuan Univ., Chengdu, China
  • fYear
    2010
  • fDate
    18-20 June 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Texture is one of the important characteristics used in identifying objects or regions of interest in an image. This paper describes some textural features based on integrated spatial gray level co-occurrence matrix, and illustrates the effectiveness of four textural features in categorizing ultrasound breast tumor images by means of Fuzzy C-means and K-medoid clustering algorithms respectively. The experimental identification accuracy is 72.6415 percent. These results indicate that textural features probably have a general applicability for classification of breast tumors.
  • Keywords
    biological organs; biomedical ultrasonics; fuzzy systems; gynaecology; image classification; image texture; medical image processing; pattern clustering; tumours; Fuzzy C-means; K-medoid clustering algorithms; integrated spatial gray level; textural feature analysis; ultrasound breast tumor images; Biomedical imaging; Breast tumors; Cancer; Clustering algorithms; Clustering methods; Image analysis; Image segmentation; Image texture analysis; Information analysis; Ultrasonic imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2151-7614
  • Print_ISBN
    978-1-4244-4712-1
  • Electronic_ISBN
    2151-7614
  • Type

    conf

  • DOI
    10.1109/ICBBE.2010.5516918
  • Filename
    5516918