文献类型：期刊文献

英文题名：A medical image fusion method based on visual models

作者：Qu, Jingyi[1]; Jia, Yunfei[1]; Du, Ying[2]

机构：[1] Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University, Tianjin 300300, China; [2] School of Science, East China University of Science and Technology, Shanghai 200237, China

年份：2012

卷号：7368 LNCS

期号：PART 2

起止页码：257

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20123415364713)

语种：英文

外文关键词：Image enhancement - Medical imaging - Color - Gaussian distribution

摘要：A new method of medical image fusion is proposed in this paper, which is based on human visual models and IHS color space. Retina-inspired difference of Gaussian model is adopted to enhance the spatial information of anatomical images. Also, 2D Log-Gabor model of primary visual cortex is used to enhance the spectrum information of functional images. The statistical analyses tools such as average gradient and entropy are demonstrated that the proposed algorithm does considerably increase spatial information content and reduce the color distortion compared to the counterpart fusion methods. In the proposed fused images the color information is least distorted, the spatial details are as clear as the original anatomical images, and the integration of color and spatial features was normal. ? 2012 Springer-Verlag.