MRI-T1 and T2 Image Fusion for Brain Image using CDF Wavelet based on Lifting Scheme

1
Abdelfatih Bengana
Abdelfatih Bengana
2
Ismail Boukli Hacene
Ismail Boukli Hacene
3
Mohamed El Amine Chikh
Mohamed El Amine Chikh
1 University of Tlemcen 13000, Algeria

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GJMR Volume 15 Issue K6

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In the field of medical imaging. Image fusion is an important application for extracting complementary information from different modality. In this work, we propose a fusion algorithm using CDF9/7 wavelet based on lifting scheme with specified fusion rules to combine pairs of multispectral Magnetic Resonance Imaging (MRI) such as T1, T2. The experimental results of brain tumor show that the proposed algorithm preserves both edge and component information and also increases the efficiency of tumor detection. The parameters like mutual information MI, entropy EN, and spatial frequency SF, standard deviation SD are calculated to evaluate performance of proposed algorithm. Finally the results are compared with existing methods.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Abdelfatih Bengana. 2016. \u201cMRI-T1 and T2 Image Fusion for Brain Image using CDF Wavelet based on Lifting Scheme\u201d. Global Journal of Medical Research - K: Interdisciplinary GJMR-K Volume 15 (GJMR Volume 15 Issue K6): .

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Crossref Journal DOI 10.17406/gjmra

Print ISSN 0975-5888

e-ISSN 2249-4618

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GJMR-K Classification: NLMC Code: WN 180
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v1.2

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January 12, 2016

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In the field of medical imaging. Image fusion is an important application for extracting complementary information from different modality. In this work, we propose a fusion algorithm using CDF9/7 wavelet based on lifting scheme with specified fusion rules to combine pairs of multispectral Magnetic Resonance Imaging (MRI) such as T1, T2. The experimental results of brain tumor show that the proposed algorithm preserves both edge and component information and also increases the efficiency of tumor detection. The parameters like mutual information MI, entropy EN, and spatial frequency SF, standard deviation SD are calculated to evaluate performance of proposed algorithm. Finally the results are compared with existing methods.

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MRI-T1 and T2 Image Fusion for Brain Image using CDF Wavelet based on Lifting Scheme

Abdelfatih Bengana
Abdelfatih Bengana University of Tlemcen 13000, Algeria
Ismail Boukli Hacene
Ismail Boukli Hacene
Mohamed El Amine Chikh
Mohamed El Amine Chikh

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