• DocumentCode
    264219
  • Title

    Numerical analysis with RK4 to detect the tumor for MRI image

  • Author

    El Kourd, K. ; Azizi, A. ; El kourd, A.

  • Author_Institution
    Lab. LI3CUB, E.P.S.T.A. Sch. of Algiers, Algiers, Algeria
  • fYear
    2014
  • fDate
    18-20 Jan. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we used numerical analysis with Runge kutta4(RK4) to study the approximation´s solutions of ordinary differential equations. This method is most popular and a good choice for common purposes because it is quite accurate, stable, and easy to program. The new data(normal & pathological images) obtained from this method is going to use it to pass to the statistical study for simple regression and for “Anova” technique to detect the tumor of MRI images. With the distribution of Gaussian curve(hypothesis test of ho)we can extract the pixels accepted in ho, then apply directly on the pathological image. The simulation program applied here is Matlab.
  • Keywords
    Gaussian distribution; Runge-Kutta methods; approximation theory; biomedical MRI; differential equations; medical image processing; regression analysis; statistical testing; tumours; Anova technique; Gaussian curve distribution; MRI image; RK4 method; Runge kutta4 method; approximation solutions; hypothesis test; numerical analysis; ordinary differential equations; pathological image; pathological images; regression technique; statistical study; tumor detect; Abstracts; Approximation methods; Color; Equations; Frequency locked loops; Magnetic resonance imaging; Anova; Numerical analysis; Runge kutta4; linear regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications & Research (WSCAR), 2014 World Symposium on
  • Conference_Location
    Sousse
  • Print_ISBN
    978-1-4799-2805-7
  • Type

    conf

  • DOI
    10.1109/WSCAR.2014.6916795
  • Filename
    6916795