For the imaging principle of multi-modal medical image, in order to make up for the shortage of the various modes of medical images, a novel medical image fusion algorithm is proposed based on the nonsubsampled contourlet transform (NSCT). Firstly, two registered source images are decomposed by the nonsubsampled contourlet transform to obtain the low frequency subband coefficients and high frequency subband coefficients. Secondly, for the low frequency subband coefficients, the fusion principle is based on the weight of local area energy. As for the high frequency subband coefficients, we choose the weight of the area standard deviation ratio as a rule. Finally, the fusion image is obtained by the nonsubsampled contourlet inverse transform. The experimental results show that the proposed method is feasible and effective, and it has better fusion performance and higher definition than the wavelet, contourlet, and wavelet+CS (CS: compressive sensing) algorithms.