扇形束CT局部成像的Lambda优质重建

Fan-Beam Lambda Imaging Without Singular Values

在CT扫描过程中,由于电离辐射作用会导致病人产生癌症或者基因损伤,所以发展低剂量的成像算法正成为热点研究。作为局部成像算法之一的Lambda成像技术,具有减少剂量与快速成像的优点,但由于奇异值的必然存在,从而降低了成像质量。基于Wang Ge局部成像算法框架,提出利用高斯核函数及卷积性质来构建新的Lambda精确成像技术,并对高斯函数的参数选择进行分析。实验结果表明,应用新算法可确保得到高质量的重建图像,其特点是消除了图像中奇异点处微分不存在的现象,使得重建图像更加连续和光滑,尤其是在重建结果中加入了抑制灰度值平均的调节项,使得图像的分辨率和对比度大大提高,更加有利于临床的诊断。

Because the ionizing radiation may induce cancers and genetic damage in the patients during CT scanning,it is highly desirable to develop an imaging algorithm for X-ray scan.As one of the local imaging techniques,the Lambda imaging reduces the X-ray dose and imaging time.However,the existence of the singular values results in the low quality of the image.In this work,we proposed a new exact Lambda imaging algorithm based on Wang（Ge＇s） local imaging method to reconstruct an image utilizing a Gaussian kernel function convoluting the projection data.We also analyzed how to choose the parameters of the Gaussian kernel function.Numerical simulations proved that our new reconstruction algorithm was with high quality,eliminating the inexistence of the differential on the singularities and enhancing the resolution and contrast of the images.