计算机科学 ›› 2011, Vol. 38 ›› Issue (12): 266-268.

• 图形图像 • 上一篇    下一篇

基于提升小波变换的医学图像融合方法

杨艳春,党建武,王阳萍,李莎,田仲泽   

  1. (兰州交通大学数理与软件工程学院 兰州730070);(兰州交通大学电子与信息工程学院 兰州730070);(兰州军区兰州总医院放疗科 兰州730050)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Medical Image Fusion Method Based on Lifting Wavelet Transform

  • Online:2018-12-01 Published:2018-12-01

摘要: 多模医学图像融合在医学图像分析和诊断上具有重要的应用价值。在对CT与MRI图像进行提升小波变换的基础上,结合低频子带系数存在区域相关性及高频子带系数的特点,提出了对于低频子带系数采用基于区域方差的融合规则,对于高频子带系数采用基于区域空间频率的融合规则,最后进行提升小波逆变换得到融合图像。实验结果表明,与传统方法相比,该方法可以有效提高医学图像融合的信息量,较好地保留了源图像的边缘及细节信息,具有良好的融合效果及量化指标。

关键词: 医学图像融合,提升小波变换,区域方差,区域空间频率

Abstract: Multimodality medical image fusion is significant in practical clinic application and therapy. According to characteristics of the regional relativity in the low-frequency sub-band and high frequency sub-band, CT and MRI images were decomposed by lifting wavelet transform. Region variance was adopted as fusion rules in the low frequency sulrband, and fusion rules based on region spatial frequency was adopted in the high frequency sub-band. Finally the fusion image was obtained by taking inverse lifting wavelet transform. Compared with the traditional methods,the results of experiment show that the algorithm enhances the fusion medical image information, effectively retains the source image edges and detail information, and the effect of fusion and quantifying indicators are fairly good.

Key words: Medical image fusion, Lifting wavelet transform, Region variance, Region spatial frectuency

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