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MRI Images Enhancement Using Genetic Programming Based Hybrid Noise Removal Filter Approach

[ Vol. 14 , Issue. 6 ]

Author(s):

Sajid Ullah Khan*, Najeeb Ullah, Imran Ahmed, Wang Yin Chai and Amjad Khan   Pages 867 - 873 ( 7 )

Abstract:


Background: Medical Resonance Imaging (MRI) images degradation is still a challenging task. The noise is a compulsory destructive factor that gets added in MRI images due to several environmental and mechanical reasons. In this paper, an effort is made and a Genetic Programming (GP) based hybrid noise removal approach is proposed which reduces the effect of Rician noise of MRI images.

Methods: The proposed approach preserves the structural and edges details of the regions of the images. The proposed GP approach uses Feature Extraction phase, GP based Optimal Expression module and Optimal Extraction based Estimation module to remove Rician noise. To validate the proposed approach, the proposed method is tested on different medical samples and the obtained results are compared with results retrieved through the existing comparative approaches.

Conclusion: The experimental results show that the proposed approach performs efficiently and can be implemented in real world applications.

Keywords:

Rician noise, genetic programming, image enhancement, MRI, optimal extraction, hybrid noise removal.

Affiliation:

FCSIT, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, CECOS University of IT and Emerging Sciences, Peshawar, Institute of Management Sciences, Peshawar, FCSIT, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, FCSIT, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak

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