Abstract: Through extracting and combining medical image information from different models of images,multi-model medical image fusion can obtain more clear,comprehensive,accurate and reliable image description on lesion site,and provide reliable basis for doctors to diagnosis of the disease and formulate reasonable treatment plan.Cloud model is a recently proposed theory in cognitive science,it has the advantage of taking the randomness and fuzziness into account,and has less application in image fusion at present.The paper introduced a method to fuse multi-model brain images such as two types MRI(Magnetic Resonance Imaging) brain image,MRI and PET(Positron Emission Tomography),MRI and SPECT(Single-Photon Emission Computed Tomography) using cloud model theory.Three steps are included in the proposed fusion method.At first,the histogram of input brain image with a smooth curve using the high-order spline function is fitted.Then the intervals in line with the valley point of the fitted curve are divided and cloud model is generated adaptively through reverse cloud generator.At last,cloud reasoning rules are designed and the fused image is gotten.The experimental results show that the characteristics of fused brain images gotten by the proposed method are clearer and the active regions are more significant than existing methods.The proposed method shows great improvement in both subjective effect and objective evaluation.

Key words: Cloud model theory,Magnetic resonance imaging,Brain image fusion,Evaluation index