Statistical Distribution To Distinguish Noise In Magnetic Resonance Images

Abstract

Fisher's test in statistics is one of the statistical tests that is used to test hypotheses, in order to ascertain whether the differences between two samples or groups are equal or unequal. In this test, the data follows a Fisher distribution, and the q test is used to compare one variance with another by partitioning. The F test can be one-tailed or two-tailed, depending on the data and parameters of the problem to be solved. The F value is obtained after conducting the test, and then it is used in conducting a one-way ANOVA test. In this article, we will talk more about the Fisher test in statistics, how to conduct the test on hypotheses, and explain the steps for conducting the test manually.
The analysis method is added to the image testing and noise determination. The distorted parts of the laboratory images are improved by adding the nonlinear filter method, which is suitable for these cases.
The nonlinear median filter demonstrates a convenient method for replacing degraded pixels. The filter is not applied to the undetected portions of the image, preserving them intact and avoiding distortion of fine image details and important edges. Experimental results have improved this architecture compared to traditional noise reduction architectures.