• DocumentCode
    1589229
  • Title

    A Combining Method for Tumors Detection from Near-infrared Breast Imaging

  • Author

    Wang, Zhicheng ; Liu, Jian ; Tian, Jinwen ; Xie, Zeping

  • Author_Institution
    Key Lab. for Image Process. & Intelligent Control, State Educ. Comm.
  • fYear
    2006
  • Firstpage
    6508
  • Lastpage
    6511
  • Abstract
    This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display of equivalent pixel curves at the part of pathological changes and display of breast tumor image edge. Accordingly, three feature extraction operators are proposed, i.e. the combination operators of anisotropic gradient and smoothing operator, an improved Sobel operator and an edge sharpening operator. Furthermore, quantitative diagnostic approaches are discussed based on blood and oxygen contents according to abundant clinical data and pathological mechanism of breast tumors. The results of clinic show that the methods of combining qualitative and quantitative diagnose are effective for breast tumor images, especially for early and potential breast cancer
  • Keywords
    biological organs; biomedical optical imaging; blood; blood vessels; cancer; feature extraction; gradient methods; gynaecology; medical image processing; oxygen; smoothing methods; tumours; O2; Sobel operator; anisotropic gradient operator; blood content; blood vessel; edge sharpening operator; feature extraction; image edge; near-infrared breast imaging; oxygen content; smoothing operator; tumor detection; Anisotropic magnetoresistance; Biomedical imaging; Blood vessels; Breast cancer; Breast tumors; Displays; Feature extraction; Pathology; Pixel; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1615990
  • Filename
    1615990