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
Link To Document :
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