Fusion of PET and MR Brain Images Based on IHS and Log-Gabor Transforms

In medical imaging, positron emission tomography (PET) shows metabolic changes of an organism in pseudo color and magnetic resonance (MR) imaging presents anatomical structures in gray level. The PET and MR brain medical image fusion produces one composite image rendering the anatomical structures with metabolic changes to help doctors effectively diagnose a possible disease. For this purpose, a new fusion method based on Intensity-Hue-Saturation model and log-Gabor wavelet transform is proposed. First, MR image and the intensity component of PET image are decomposed by log-Gabor wavelet transform with suitable decomposition scale. Then, maximum selection' fusion rule for the high-frequency sub-band and two-stage fusion rule based on weighted-averaging scheme and visibility measure for the low-frequency sub-band are employed. Finally, a new intensity component, obtained by applying reverse log-Gabor wavelet transform to the fused high-and low-frequency sub-bands, along with original hue and saturation components of PET image are converted to obtain our fused color image. In our fused images, both anatomical structures and color changes are rendered with effectively-reduced color distortion. Experimental results on twelve sets, including normal axial, normal coronal, and Alzheimer's disease brain images, demonstrate that our fusion method outpaces framelet-transform-based method both visually and quantitatively.