基于小波的DSA融合脑血管图提取

Saba Momeni, H. Pourghassem
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引用次数: 1

摘要

近年来,图像融合在医学图像处理中具有突出的应用作用。采用数字减影血管造影(DSA)图像显示血管图。提出了一种基于离散小波变换系数的DSA序列图像融合算法。我们的算法将比较不同的小波变换和高频系数的活动准则。这些比较是基于客观的评价标准来衡量融合结果与参考图像之间的噪声存在程度、清晰度和相关性。最后,我们明确了哪种类型的小波变换和活动准则能得到更丰富的脑血管图信息。
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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 paper, a new fusion algorithm for DSA serial images based on discrete wavelet transform coefficients is proposed. 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, we specify which type of wavelet transform and activity criterion results more informative brain blood vessel map.
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