• DocumentCode
    2524493
  • Title

    A BREAST MRI BIOMARKER FOR CYSTS AND INFILTRATING DUCTAL CARCINOMAS

  • Author

    Ketsetzis, Georgios ; Brady, Michael

  • Author_Institution
    Dept. of Eng. Sci., Oxford Univ.
  • fYear
    2007
  • fDate
    12-15 April 2007
  • Firstpage
    1268
  • Lastpage
    1271
  • Abstract
    Parametric MR information from tissues is known to increase the specificity of segmentation resulting from contrast enhanced MR studies. Rapid signal acquisition methods, such as FSPGR, prevent the extraction of complete parametric information; this in turn limits the specificity that can be achieved from dynamic breast MR studies. We introduce a biomarker k, which combines pseudo-proton density and T2* information. Following tissue segmentation by two experts and removal of the bias field, we compute k for each tissue type for 83 patients. A Gaussian distribution model for k for each tissue is used to detect cysts and infiltrating ductal carcinomas (IDCs) using a 95% confidence interval in new cases. The method yields encouraging results in both cases
  • Keywords
    biomedical MRI; gynaecology; image segmentation; medical image processing; physiological models; Gaussian distribution model; breast MRI biomarker; cysts; infiltrating ductal carcinomas; pseudo-proton density; tissue segmentation; Biomarkers; Breast; Cancer; Current measurement; Lesions; Magnetic resonance imaging; Mathematical model; Pathology; Time measurement; Tumors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    1-4244-0672-2
  • Electronic_ISBN
    1-4244-0672-2
  • Type

    conf

  • DOI
    10.1109/ISBI.2007.357090
  • Filename
    4193524