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Objective We use the method of image fusion combining anatomical and functional medical images to provide more useful information and to help the doctors in diagnosis. Methods Sparse representation can reflect the advantage of the image feature well. First, the CT and MRI images of cerebral infarction and cerebral hemorrhage from the hospital are selected, and the algorithm based on double sparse dictionary is used to obtain the sparse dictionary. Then the method of max selection with information of spatial domain as the fusion rule fuses the selected clinical images. Finally, the results of the proposed method are compared with the results of PCA method and DWT method in the subjective aspect and the objective aspect on the indices of QAB/F and Piella. Results Subjective evaluations of the fusion images obtained from the proposed method are better than the other two methods, and the mean values of QAB/F and Piella in the objective aspect are 0.9139 and 0.7213, which are superior to the other two methods. Conclusions The fusion images obtained from the proposed method based on sparse dictionary are clearer, with higher contrast, and have more features of source images, which is helpful in diagnosis.