• DocumentCode
    554034
  • Title

    MVN_CNN and UBN_CNN for endocardial edge detection

  • Author

    Ketout, H. ; Gu, Jhen-Fong ; Horne, Gary

  • Author_Institution
    Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
  • Volume
    2
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    781
  • Lastpage
    785
  • Abstract
    In this paper, Universal Binary Neurons Cellular Neural Networks (UBN_CNN) endocardial edge detection is proposed. The echocardiographic image is preprocessed to enhance the contrast and smoothness by utilizing Multi Valued Neural Cellular Neural Networks (MVN_CNN) non linear filter. UBN_CNN is applied to the smoothed image to extract the heart boundaries. A non threshold Boolean function with nine variables is utilized to detect the edges corresponding to the upward and downward brightness overleaps. Some experimental results are given for different echocardiographic images. The combination of MVN_CNN and UBN_CNN approach showed better results for extracting the LV endocardial boundaries.
  • Keywords
    Boolean functions; biomedical ultrasonics; cellular neural nets; edge detection; feature extraction; image enhancement; medical image processing; nonlinear filters; LV endocardial boundary extraction; MVN_CNN; UBN_CNN; contrast enhancement; echocardiographic image; endocardial edge detection; heart boundary extraction; multivalued neural cellular neural networks; nonlinear filter; nonthreshold Boolean function; smoothness enhancement; universal binary neurons cellular neural networks; Cellular neural networks; Equations; Heart; Image edge detection; Neurons; Nonlinear filters; CNN; Echocardiography; Endocardial; MVN_CNN; UBN_CNN; artifacts; edge detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2011 Seventh International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4244-9950-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2011.6022163
  • Filename
    6022163