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Comparative Study of Different Wavelet Transforms in Fusion of Multimodal Medical Images

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
R. E. Masumdar, R. G. Karandikar

R E Masumdar and R G Karandikar. Comparative Study of Different Wavelet Transforms in Fusion of Multimodal Medical Images. International Journal of Computer Applications 146(11):18-24, July 2016. BibTeX

	author = {R. E. Masumdar and R. G. Karandikar},
	title = {Comparative Study of Different Wavelet Transforms in Fusion of Multimodal Medical Images},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2016},
	volume = {146},
	number = {11},
	month = {Jul},
	year = {2016},
	issn = {0975-8887},
	pages = {18-24},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2016910899},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This paper presents a comparative study of image fusion of MRI and CT images using various wavelet transforms. The fusion of the images is done by implementing a multi-resolution decomposition method with the help of various wavelets. Entropy, PSNR and MSE are the parameters that are used as performance metrics of the fusion done using various wavelets. The MRI and CT images are then fused using the select maximum fusion rule, since studies have shown that select maximum rule provides the best result. The final fused image is examined using the various performance metrics to evaluate which wavelet gives the best result.


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Computed Tomography, Magnetic Resonance Imaging, Wavelet Transform, Haar Transform, Daubechies Transform, Symlet Transform, Image Fusion Vanishing Moments, Multiresolution Decomposition, Image Fusion, Quadrature Mirror Filter, Order, Filter Banks, Mean Squarred Error, Peak Signal to Noise Ratio, Entropy