Study On Registration And Fusion Multimodality Medical Image

With the rapid development of imaging technology, the modality medical images have been used widely in clinical diagnoses and surgical therapies. Because of a different imaging mechanism and highly complexity of body tissues and structures, single-modality medical image can not provide enough information for clinical doctors. Different modality medical images provide non-overlay complementary information. Integrating those images is helpful to improve the accuracy of clinical diagnoses and surgical therapies.Image registration is the first and key part of problem to be solved in the integrations. When the spatial position of two medical images is same, the registration could be achieved. Then the initial zoom parameter and search for the best matching parameters were set to make the mutual information maximal, using improved simplex method with the mutual information as the comparability criterion. Maximum of mutual information, the registration reach the best. Based on the results of test, improved simplex method can adjust reflecting distance. Stepped-up optimization algorithm on the new experimental points through the methods of"reflection","enlargement","shrinkage"or"global systolic". The experiment of anatomic images and functional images, result shows that this algorithm doesn't need manual pre-adjustment of image resolution. So it has high degree of automation and the advantage of high registration speed and high registration accuracy. It can meet the demand of multi-modality image registration well during the research of human brain atlas.After registration the medical images are fusion by wavelet transforms. For high frequency fusion, the new coefficients are selected by those coefficients with maximum absolute values in two original images. For low frequency fusion, it is used to combine with bases on domain pixel correlation and regional variance. The result show that the fusion image is clearer, details are more abundant, the lesions display obvious, relatively position accurate. It reflects that multi-information is the more overall and supplementing each other. More information could be utilized to make more accurate diagnosis. It is useful for clinical medicine and diagnosis.