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Article type: Research Article
Authors: Faragallah, Osama S.a; * | Muhammed, Abdullah N.b | Taha, Taha S.c | Geweid, Gamal G.N.d; e
Affiliations: [a] Department of Information Technology, College of Computers and Information Technology, Taif University, Saudi Arabia | [b] Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt | [c] Department of Electronics and Communication Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt | [d] Department of Biomedical Engineering, College of Engineering and Computer Sciences, Marshall University, Huntington, WV, USA | [e] Department of Electrical Engineering, Faculty of Engineering, Benha University, Benha, Egypt
Correspondence: [*] Corresponding author. Osama S. Faragallah, Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia. Tel.: +966 540923647; E-mail: [email protected].
Abstract: This paper presents a new approach to the multi-modal medical image fusion based on Principal Component Analysis (PCA) and Singular value decomposition (SVD).The main objective of the proposed approach is to facilitate its implementation on a hardware unit, so it works effectively at run time. To evaluate the presented approach, it was tested in fusing four different cases of a registered CT and MRI images. Eleven quality metrics (including Mutual Information and Universal Image Quality Index) were used in evaluating the fused image obtained by the proposed approach, and compare it with the images obtained by the other fusion approaches. In experiments, the quality metrics shows that the fused image obtained by the presented approach has better quality result and it proved effective in medical image fusion especially in MRI and CT images. It also indicates that the paper approach had reduced the processing time and the memory required during the fusion process, and leads to very cheap and fast hardware implementation of the presented approach.
Keywords: Image fusion, PCA, SVD, medical images, fusion
DOI: 10.3233/JIFS-202884
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 4021-4033, 2021
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