医学图像融合算法的应用与研究

Research and application of medical image fusion algorithm

目的:不同的医学影像为医生提供不同的医学信息,图像融合技术逐渐成为临床诊断和医学研究的重要手段。方法:本文采用了一种基于不可分离小波框架的图像融合算法。算法首先对已配准的医学图像进行非分离小波分解,把图像分解成低频和高频子图像,针对高频分量和低频分量不同的特点,采用不同的融合规则对其进行融合,最后进行小波逆变换,得到最终的融合图像。此外,文中引入了熵、平均梯度,融合均匀度对融合图像进行评价。结果:实验结果表明,本文算法获得的融合图像包含更丰富、更全面的细节信息,优于传统的小波变换方法。结论:采用基于不可分离小波框架的图像融合算法是一种有效的医学图像融合方法,提高了疾病诊断的准确性和正确性。

Objective：Doctors can get different details from different medical images because of the different imaging theory of medical instruments and application,image fusion become a key means in clinic diagnose and medical research.Methods：This paper adopted an image fusion method based on non-separable wavelet frame transform.Firstly,having finished the registration,medical image was decomposed with non-separable wavelet decomposition,and into low and high frequency sub-image.According to the different characteristics of high frequency and low frequency components,the paper acquire different fusion rule to fuse the images,then through the inverse wavelet transform,we can acquire the fused image.In addition,the paper introduced the entropy,average gradient,uniformity of fusion to evaluate the fused image.Results：The results showed that this method could enhance the detail and brightness information of fused image,which is superior to traditional wavelet transform.Conclusion：It is an effective method of medical image fusion based on the non-separable wavelet framework image fusion algorithm,which could improve the accuracy and validity of disease diagnosis.