Kang Yuanyuan, Li Bin, Tian Lianfang, Mao Zongyuan
College of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2009 Apr;26(2):244-7, 252.
Multi-modal medical image fusion has important value in clinical diagnosis and treatment. In this paper, the multi-resolution analysis of Daubechies 9/7 Biorthogonal Wavelet Transform is introduced for anatomical and functional image fusion, then a new fusion algorithm with the combination of local standard deviation and energy as texture measurement is presented. At last, a set of quantitative evaluation criteria is given. Experiments show that both anatomical and metabolism information can be obtained effectively, and both the edge and texture features can be reserved successfully. The presented algorithm is more effective than the traditional algorithms.
多模态医学图像融合在临床诊断和治疗中具有重要价值。本文将Daubechies 9/7双正交小波变换的多分辨率分析引入到解剖图像和功能图像融合中，进而提出一种将局部标准差和能量相结合作为纹理测度的新型融合算法。最后给出了一套定量评估标准。实验表明，该算法能够有效获取解剖信息和代谢信息，成功保留边缘特征和纹理特征，且比传统算法更有效。
