PCA-DWT based medical image fusion using non sub-sampled contourlet transform

Multimodal medical image fusion is used to minimize the redundancy while increasing the necessary information from the input images obtained using different medical imaging sensors. The sole aim is to yield a single fused image, which could be more informative for an efficient analysis. This paper presents a two-stage fusion framework using the cascaded combination of Discrete wavelet transform(DWT) and Non sub-sampled Contourlet transform (NSCT) domains for images acquired using two distinct medical imaging modalities (i.e., magnetic resonance imaging and computed tomography scan). The first stage employs a principal component analysis algorithm in DWT domain to minimize the redundancy. At second stage Maximum fusion rule is then applied in NSCT domain to enhance the contrast of the diagnostic features. A quantitative analysis of fused image is carried out using fusion metrics.