A novel technique of medical Image Fusion using Stationary Wavelet Transform and principal component analysis

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This paper presents a novel medical image fusion technique named as hybrid technique developed by combining the features of principal component analysis (PCA) and stationary wavelet transform (SWT) fusion rules. Magnetic resonance imaging (MRI) and computed tomography (CT) images are merged to acquire contemporary image that augments the supplementary information to the consultant for better diagnosis. In this work, fusion results of proposed hybrid technique are compared with those using PCA and SWT techniques. The performance evaluation is carried out in terms of Mean (M), Standard deviation(SD), Entropy (H), Average gradient(AG), Root mean square error (RMSE), Peak signal to noise ratio (PSNR), Mutual Information (MI) and spatial frequency(SF). Comparison result demonstrates a better performance using hybrid technique than that of other two methods (PCA and SWT).