F-Test and One-Way ANOVA for Medical Images Diagnosis

Authors

Jamal Kamil K. Abbas, Cybersecurity Engineering Techniques, Al-Nisour University College, Baghdad, IraqFollow
Ali Abdulkadhum Ruhaima, Mathematics Department, College of Sciences, University of Baghdad, Baghdad, Iraq
Omer Abdulhaleem Naser, Cybersecurity Engineering Techniques, Al-Nisour University College, Baghdad, Iraq
Dunya Mohee Hayder, Department of Mathematics and computer applications, college of sciences, Al-Nahrain University, Jadriya, Baghdad, Iraq

Abstract

This paper introduces a new method for the discrimination of impulse noise in medical MRI images. Statistical F-distribution by means of Monte Carlo simulation for forecasting the location of Impulse noise on distorted images is employed. The adaptive noisy pixels are identified as noisy using One-Way ANOVA hypothesis method while the rest of the noisy pixels are selective noisy pixels. Thus, the statistical prediction method is used to predict the noise location on the test images. The distorted portions in the images predicted by this structure are then made better by applying a right kind of nonlinear filtering. The nonlinear median filter is advisable for demonstrating a suitable way of the replacement of the degraded pixels. The filter is not applied to the not-detected regions of the image to remain the same so that delicate details and edges are not spoiled. Experimental results enhanced this structure as it is compared to the classical noise reduction structures.

First Page

29

Last Page

38

Recommended Citation

Abbas, Jamal Kamil K.; Ruhaima, Ali Abdulkadhum; Naser, Omer Abdulhaleem; and Hayder, Dunya Mohee (2024) "F-Test and One-Way ANOVA for Medical Images Diagnosis," Al-Nisour Journal for Medical Sciences: Vol. 6: Iss. 2, Article 5.
DOI: https://doi.org/10.70492/2664-0554.1004