• DocumentCode
    1686184
  • Title

    Implementation of an improved cellular neural network algorithm for brain tumor detection

  • Author

    Abdullah, Azian Azamimi ; Chize, Bu Sze ; Nishio, Yoshifumi

  • Author_Institution
    Sch. of Mechatron. Eng., Univ. Malaysia Perlis (UniMAP), Arau, Malaysia
  • fYear
    2012
  • Firstpage
    611
  • Lastpage
    615
  • Abstract
    Image processing plays an important role in medical diagnosis. In this paper, a brain tumor detection method based on cellular neural networks (CNNs) is proposed. Brain tumor is an abnormal growth of cells inside the skull. To examine the location of tumor in the brain, Magnetic Resonance Imaging (MRI) is used. Radiologists will evaluate the grey scale MRI images. This procedure is really time and energy consuming. To overcome this problem, an automated detection method for brain tumor using CNN is developed. By using the template in the CNN simulator, output of the desired image can be performed. Therefore, many templates were combined in order to obtain an accurate result that will help radiologists detecting the tumor in brain images easily.
  • Keywords
    biomedical MRI; brain; cellular biophysics; cellular neural nets; medical image processing; tumours; automated detection method; brain tumor detection; cells; cellular neural network algorithm; grey scale MRI images; image processing; magnetic resonance imaging; medical diagnosis; skull; Algorithm design and analysis; Brain; Cellular neural networks; Image segmentation; Magnetic resonance imaging; Signal processing algorithms; Tumors; Brain tumor; MRI images; cellular neural network; image processing; templates;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering (ICoBE), 2012 International Conference on
  • Conference_Location
    Penang
  • Print_ISBN
    978-1-4577-1990-5
  • Type

    conf

  • DOI
    10.1109/ICoBE.2012.6178990
  • Filename
    6178990