针对线阵工业CT重建图像中环形伪影干扰问题，设计一种基于多元统计的新型校正方法。首先采用灰度直方图统计结合最大类间方差法对CT图像中不同材料密度进行分类，根据材料密度分布对原始CT图像进行材料去除，然后进行极坐标系转换，对转换后的极坐标图像进行横坐标像素值统计，提取不同半径r下伪影灰度幅值统计值，最后采用原始CT图像消减伪影统计值的方式进行伪影校正。采用6 MeV线阵探测器高能工业CT系统，对含有环形伪影的不同结构CT图像进行校正试验。试验结果表明：该方法在有效去除CT图像环形伪影的同时，还能较好地保持图像细节和分辨率，显著提高了处理速度。

A multivariate statistical method was proposed to correct ring artifacts in industrial CT images. First, the grayscale histogram statistics and maximum interclass variance were used to classify the density in CT images. Then, the coordinate system was converted to the polar one and the abscissa pixel values were counted in the polar coordinate image and the artifacts of the gray scale amplitude were extracted at different radii. Finally, the correction was performed by subtracting artifacts from the original CT image. The CT images of different structures with ring artifacts were calibrated by using 6 MeV linear array detector high energy industrial CT system. The experimental results show that this method can effectively remove CT images from ring artifacts. The image details and resolution were well kept and the processing speed was significantly improved.