基于Contourlet变换的医学图像检索

Medical Image Retrieval Based on Contourlet Transform

针对医学图像特点,提出了一种基于纹理的医学图像检索算法.Contourlet变换结合了不可分离的方向滤波器组,具备多尺度和多方向特性,能有效地捕获到图像中的轮廓,并对其进行稀疏表示.本算法充分利用图像Contourlet变换系数的统计特征,形成描述纹理特征的特征向量,并将其作为检索的特征向量.采用上述算法对CT图像数据库进行了检索实验,并与基于小波变换纹理分析方法进行了比较.结果表明,在Contourlet变换域上检索查准率高于在小波域上的查准率,从而验证了该算法具有良好的检索性能.

Considering the characteristics of medical image, a novel medical image retrieval algorithm based on texture is proposed. Combining with the multi-scale and multi-directional characteristics of non-separable and directional filter banks, the contourlet transform can effectively capture the contours of an image and depict them sparsely. The algorithm proposed takes fully the advantage of statistical attribution of image＇s contourlet transform coefficients to form the eigenvector for depicting textural feature and retrieval. Retrieval tests were carried out for a CT image database with the algorithm, and the results were compared with that by the retrieval algorithm based on Harr wavelet transform. It was found that the precision of retrieval in contourlet transform domain is higher than that in wavelet transform domain, thus verifying the higher retrievability of the algorithm.