• DocumentCode
    2180007
  • Title

    Improving the Discrimination of Benign and Malignant Breast MRI Lesions Using the Apparent Diffusion Coefficient

  • Author

    McClymont, Darryl ; Mehnert, Andrew ; Trakic, Adnan ; Crozier, Stuart ; Kennedy, Dominic

  • Author_Institution
    Sch. of lTEE, Univ. of Queensland, Brisbane, QLD, Australia
  • fYear
    2010
  • fDate
    1-3 Dec. 2010
  • Firstpage
    569
  • Lastpage
    574
  • Abstract
    This paper presents an investigation of the apparent diffusion coefficient (ADC) for improving the discrimination of benign and malignant lesions in breast magnetic resonance imaging (MRI). In particular a method is presented for automatically selecting hyper intense tumour voxels in dynamic contrast enhanced (DCE) MRI data and evaluating their average ADC in the corresponding diffusion-weighted (DW) MRI data. The method was applied to ten breast MRI datasets obtained from routine clinical practice. The results demonstrate that the combination of the relative signal increase (DCE-MRI) with the apparent diffusion coefficient (DW-MRI) leads to better discrimination than with either feature alone. The results also suggest that it is important to acquire the DW-MRI data in a consistent fashion, i.e. either before or after the acquisition of the DCE-MRI data.
  • Keywords
    magnetic resonance imaging; medical image processing; apparent diffusion coefficient; benign breast MRI lesions; diffusion weighted MRI data; dynamic contrast enhanced MRI data; hyper intense tumour voxels; magnetic resonance imaging; malignant breast MRI lesions; MRI; apparent diffusion coefficient; breast cancer; contrast enhancement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Image Computing: Techniques and Applications (DICTA), 2010 International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-1-4244-8816-2
  • Electronic_ISBN
    978-0-7695-4271-3
  • Type

    conf

  • DOI
    10.1109/DICTA.2010.101
  • Filename
    5692622