Statistical Testing of Different Fusion Techniques on MRI & CT Images
A Somasekhar1, P Subbaiah2

1A Somasekhar, Research Scholar, Rayalaseema University, Kurnool,
A.P, India.
2P Subbaiah, Professor, Nalla Narasimhareddy College of Engineering,
Hyderabad, Telangana, India.

Manuscript received on 04 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 7133-7135 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6071098319/2019©BEIESP | DOI: 10.35940/ijrte.C6071.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Image fusion unites data from various modalities of identical prospect in to a single data retaining the significant and necessary features from each of the unique image. These days, with the hasty progress in high end technologies with contemporary instruments, has turn out to be a essential factor of a outsized numeral of applications, plus analysis, examine, and handling. Image fusion on medical field is the initiative progress of the picture substance by integrating data took from dissimilar picture tools like CT, MRI. MRI gives enhanced data on malleable hankie with lot of misrepresentation. But, one sort of picture might not be adequate to afford precise scientific necessities for the physicians. Therefore, the fusion of the different medicinal pictures is essential. In this work Static analysis of diverse fusion techniques are done with the help of parameters like Mean, Entropy, Correlation coefficient, Standard deviation, and covariance.
Keywords: Fusion, MRI, CT, Mean, Entropy, Correlation Coefficient, Standard Deviation, Covariance.

Scope of the Article:
Image Processing and Pattern Recognition