Study On Method Of Medical Image Fusion

which are captured by multiple sensors on the same target or scene are processed the integrated treatment of appropriate according to an algorithm. That can obtain a new image which satisfies certain requirements. And this image usually can not be obtained by a single sensor. Medical image fusion is a very unique application of image fusion. With the rapid development of the medical imaging, multiple advanced medical imaging equipments provide more modality of medical imaging information for clinical diagnosis. Medical image fusion takes full advantage of the complementary information between multimodal images to make clinical diagnosis and treatment more accurate and complete.Focus of this study is that medical image fusion at pixel level. Firstly, it introduced the concept, significance, research status of medical image fusion, then described the hierarchical model, common methods and classification of image fusion. And researched the principles of medical image fusion based on wavelet transform. Starting from the development of wavelet theory, introduced the basic theory of wavelet, two-dimensional image wavelet decomposition and reconstruction, the general principle of medical image fusion based on wavelet transform and integration steps.This paper discusses the impact of different wavelet bases and different fusion rules to the quality of the fusion image, and proposes a medical image fusion algorithm based on regional variance and multi-wavelet bases. Then conducted the corresponding simulation experiments according to the proposed method, and using the evaluation criteria described in the text to demonstrate the superiority of the proposed method.Finally, researched the image fusion based on wavelet-Contourlet transform, and conducted medical image fusion simulation based on Contourlet transform and wavelet-Contourlet transform.