Brain Blood Vessel Map Extraction Using Wavelet-based DSA Fusion

Recently image fusion has prominent and applicable roles in medical image processing. Digital subtraction angiography (DSA) image is applied to display map of blood vessels. In this essay، a new fusion algorithm for DSA serial images based on discrete wavelet transform coefficients is proposed. Fusion of high frequency coefficients is based on proposed fusion map and four evaluation criteria which introduce level of coefficient''s energy. Our algorithm will be compared for different wavelet transforms and activity criteria for high frequency coefficients. The comparisons are based on the objective evaluation criteria which show measure of noise existence، sharpness and correlation between the fusion result and reference image. Finally، Meyer discrete wavelet transform is resulted as the best wavelet transform، and sum of modified Laplacian، local energy are introduced as activity level measurment for high and low frequency coefficients in process of brain vessel map extraction.