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Evaluation of Spatial and Transform Fusion methods for Medical Images using Normalized Non-Reference Quality Metrics

by R. Barani, M. Sumathi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 143 - Number 13
Year of Publication: 2016
Authors: R. Barani, M. Sumathi
10.5120/ijca2016910510

R. Barani, M. Sumathi . Evaluation of Spatial and Transform Fusion methods for Medical Images using Normalized Non-Reference Quality Metrics. International Journal of Computer Applications. 143, 13 ( Jun 2016), 21-28. DOI=10.5120/ijca2016910510

@article{ 10.5120/ijca2016910510,
author = { R. Barani, M. Sumathi },
title = { Evaluation of Spatial and Transform Fusion methods for Medical Images using Normalized Non-Reference Quality Metrics },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 143 },
number = { 13 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 21-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume143/number13/25137-2016910510/ },
doi = { 10.5120/ijca2016910510 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:46:18.539415+05:30
%A R. Barani
%A M. Sumathi
%T Evaluation of Spatial and Transform Fusion methods for Medical Images using Normalized Non-Reference Quality Metrics
%J International Journal of Computer Applications
%@ 0975-8887
%V 143
%N 13
%P 21-28
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical image fusion is a method which enhances the image content by combining the images obtained using different imaging modalities like Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT). The main objective of medical image fusion is to extract and merge the useful information from multi-modality medical images thus highlighting the significant features for improved prediction of the scenario for treatment planning. In this paper, the different image fusion techniques in spatial and transform domain are implemented for MRI/CT and PET/CT images. The resultant fused images are analyzed with non-reference image quality metrics: Entropy (EN), Standard Deviation (SD), Peak Signal to Noise Ratio (PSNR), Spatial Frequency (SF), Average Gradient (AG), Edge Strength (ES), Fusion Factor (FF) and Fusion Symmetry (FS). It is found that the image fusion using Discrete Wavelet Transform (DWT) outperforms all the other spatial and pyramid based fusion methods.

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Index Terms

Computer Science
Information Sciences

Keywords

medical image fusion spatial fusion transforms fusion non-reference quality metrics.

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