中文摘要：

近年来，用于从多模医学图像数据中挖掘有用信息的融合算法不断被提出．但是，还没有一种合适的算法用于医学解剖和功能像的融合．基于此，提出一种基于小波变换的新方法，用于医学解剖和功能像的融合．选择高频系数时，通过计算各子图像的全局梯度来实现高频信息的融合，使融合后的图像较好地保留解剖结构所对应的功能信息；低频系数采用基于邻域能量的融合算法，保留解剖图像的边缘和纹理特征．实验结果和评价参数表明，这种改进的医学图像融合算法强化了融合图像的边缘和纹理特征，有效地保留了原图像的解剖信息和功能信息．

英文摘要：

In recent years, many medical image fusion methods had been exploited to derive useful information from multimodality medical image data. But, there isn＇t an appropriate fusion algorithm for anatomical and functional medical image. The traditional method of wavelet fusion is improved and a new algorithm of anatomical and functional medical image fusion is proposed. When choosing high frequency coefficients, the global gradient of each sub-image is calculated to realize fusion, so that the fused image could reserve the functional information; while the low coefficients choosing is based on the analysis of the neighbor region energy, retain the edge and texture feature of the anatomical image. Experimental results and the quality evaluation parameters show this improved fusion algorithm enhance the edge and texture feature and retain function information and anatomical information effectively.