Study with RK4 & ANOVA the location of the tumor at the smallest time for multi-images

E. Kaouther, S. Khelil, S. Hammoum
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引用次数: 4

Abstract

In this paper, we have translated a nonlinear model to linear one by used the numerical analysis with Runge-Kutta 4 modify (RK4). This method is the most popular, where the step size H is working to increase the lighting of the image compared with the original picture. After that, we passed to the statistical study for linear regression then for the analysis of variance, or more briefly “ANOVA technique”, where we have used the statistical study on the pathological image to detect the tumors of multi MRI images and extract the place of lesion by two ways: distribution of Gaussian curve (hypothesis test of h0) and directly on the pathological image then compared the result obtained for nonlinear model with linear one. The simulation program applied with Matlab.
利用RK4和方差分析研究多幅图像在最小时间内的肿瘤位置
本文采用龙格-库塔4修正(RK4)的数值分析方法,将非线性模型转化为线性模型。这种方法是最流行的,其中步长H是为了增加图像与原始图片相比的照明。之后,我们进行了线性回归的统计研究,进行方差分析,或者更简单地说“ANOVA技术”,我们利用病理图像的统计研究,通过高斯曲线分布(假设检验为0)和直接对病理图像进行两种方法检测多幅MRI图像的肿瘤并提取病变位置,然后将非线性模型得到的结果与线性模型得到的结果进行比较。该仿真程序应用于Matlab。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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