Fusion of multimodality Medical Images using combined Activity Level Measurement and Contourlet Transform

In this paper, we propose a novel multimodality Medical Image Fusion (MIF) method, based on a novel combined Activity Level Measurement (ALM) and Contourlet Transform (CNT) for spatially registered, multi-sensor, multi-resolution medical images. The source medical images are first decomposed by CNT. The low-frequency subbands (LFSs) are fused using the novel combined ALM, and the high-frequency subbands (HFSs) are fused according to their `local average energy' of the neighborhood of coefficients. Then inverse contourlet transform (ICNT) is applied to the fused coefficients to get the fused image. The performance of the proposed scheme is evaluated by various quantitative measures like Mutual Information (MI), Spatial Frequency (SF), and Entropy (EN) etc. Visual and quantitative analysis and comparisons show the effectiveness of the proposed scheme in fusing multimodality medical images.