Fuse the Multimodality Medical Images using Transforms with Neuro Fuzzy based Hybrid Fusion Techniques

Abstract

A great challenge in medical image processing is combining the complement pathological features into a single image. Various issues are faced by the images that undergo fusion. Some examples are the way the fusion artifacts, appear, edge strength, contrast of input medical image finally the cost of computation. Here the input image is decomposed by applying Non-Subsampled Contourlet Transform (NSCT) The averaging fusion rule with type two fuzzy logic is employed in components of lower frequency. The maximum fusion rule with PCNN is applied in components of high frequencies. The inverse transforms and coefficients of frequency bands are used to derive fused image. The best diagnosis of the health issues from the given sources’ are obtained from the fused image.