Fusion ofimages has an important role in medical image diagnosis. Medical imaging systems have some limitations due to degradations and noise. Hence, it is necessary to apply some techniques such as image fusion to integrate information from different image modalities into the fusion result. With this strategy, the image features will be more defined, and this in turn, helps for better diagnosis. This paper presents an image fusion technique for different kinds of images to enhance the quality of brain tumor images. This technique depends on convolutional neural network (CNN) with more layers to obtain high-quality images for better diagnosis. The learning process of the CNN helps to measure the activity level and fusion ratio. The obtained fusion resultsare compared with thoseof traditional fusion methods. Different quality evaluation metrics are used in the assessment of the proposed technique.