DISPLAY THE DISEASE PLACE FOR NON LINEAR MODEL WITH “ ANOVA” TECHNIQUE
Résumé
ABSTRACT
In this paper, we transform a nonlinear model to a linear one by using numerical analysis with ‘‘Runger-Kutta4(RK4)’’. Which
is a mathematical technique to approximate solution of ordinary differential equations; this method is most popular where the
step size H is working to increase the lighting of the image compared with the original picture. The new data (normal &
pathological images) obtained from this method is used in the statistical study of simple regression and “ANOVA” technique
to detect the tumor of MRI images. After that, we study the linear regression and “ANOVA” technique by using ANOVA
statistical test (equation of ANOVA: fcal) and compare it with ANOVA table(ftab) for probability p-value =0.01 (here for
area 200x200, ftab=1) and see all pixels inferior to‘’1’’ that means the hypothesis ho is accepted. All these detail is to extract
the place of the lesion on MRI ,(which contain matrix data of normal image and pathological ones), the extract the accepted
ho pixels directly on the pathological image. The simulation program applied here is Matlab.
KEYWORDS: Runge kutta ,linear regression, Anova.
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