The Fusion Technology Research For Medical Functional And Structure Image Based On Wavelet Transform

Medical image fusion, a subject which involves information science and medical imaging science, is a hot spot in medical image processing. Structure image and functional image are the most common image in clinic disease diagnose. Using information…medical image can access richer, can access richer,more intuitive, more comprehensive details information and the metabolic information of tissues and organs, which provides the basis for early diagnosis of disease and functional areas precise positioning, and improves the accuracy and correctness for disease diagnosis and treatment.In this paper, the major research is based on the medical structure image and medical function image fusion technology. The purpose is exploring a more efficient algorithm used in the fusion of anatomical image and functional image based on studying the existing fusion algorithm, which make the result image not only retain the details of the anatomical structure information, but also the functional information of organization. First, it discusses the theory and characteristics of traditional medical image fusion methods and analyses the limitations and the shortcomings with the experimental results. Then, the focus on analysis of image fusion based on wavelet transform technology, for the limitations of the traditional wavelet transform in medical function and structure image, two new methods of medical image fusion which high frequency and low frequency coefficients are studied respectively are presented. Experimental results show the effectiveness and feasibility of new methods. Finally, the new method have been used in CT perfusion image and MRI image fusion, to extract the blood flow information in Parkinson's rats brain, and provide more accurate and effective information for clinical diagnosis.This topic covers the new innovation in improving image fusion method based on wavelet transform, making it suitable for the medical structure and functional image fusion. In the context of integral organization edge and clear function areas, the wavelet transform method based on edge details is used. This method is simple, easy to implement, and have good fusion results. In the context of weak organization edge and unintelligible function areas, the wavelet transform method based on gradient is used. This method can obtain a better fusion results, and apply in a wider scope.