• DocumentCode
    3591354
  • Title

    Feasibility of multi-layered perceptron network in discriminating breast magnetic resonance imaging lesions

  • Author

    Muthyala, Sreenivas ; Gibbs, Peter ; Turnbull, Lindsay

  • Author_Institution
    Centre for MR Investigations, Hull Univ., UK
  • Volume
    4
  • fYear
    2005
  • Firstpage
    2493
  • Abstract
    The feasibility of IMLP networks in reliably discriminating between benign and malignant lesions is demonstrated in this pilot study. MLP networks can be trained on similar information that a radiologist would use to interpret lesions on DCE-MRI study of breast and perform as well as a trained radiologist. In the future this work will be extended to a larger data set, and the feasibility of other neural networks such as radial basis function will be tested.
  • Keywords
    diseases; magnetic resonance imaging; medical computing; medical image processing; multilayer perceptrons; breast magnetic resonance imaging lesions; multi-layered perceptron network; neural networks; radial basis function; Breast cancer; Intelligent networks; Lesions; Magnetic resonance imaging; Mammography; Multilayer perceptrons; Neural networks; Tellurium; Testing; X-ray imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-9048-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.2005.1556294
  • Filename
    1556294