Abstract: The main purpose of medical image fusion is to obtain a high resolution image with as much details as possible for diagnosis. Magnetic resonance (MR) and computed tomography (CT) medical images has special sophisticated and complementary characteristics which are required for accurate diagnosis of disease. Based on this, a new medical fusion approach for MR and CT images based on multi-scale coefficient decomposition framework was proposed. The proposed approach used a combination of discrete wavelet and non-subsampled shearlet transforms for the initial multi-scale decompositions firstly. The decomposition multi-scale coefficients were fused twice using various local activity measures. The fused image was reconstructed by inverse transform of the approximation coefficients in the NSST domain and inverse wavelet transform of fused approximation and fused detail coefficients. The simulation results show that, compared with the state-of-the-art method, the fusion image with higher quality and less computation overhead which can be helpful for better medical diagnosis is obtained in the proposed method.

Key words: medical image fusion, multi-scale decomposition, MR image, CT image, activity measure