基于半扇束扫描的CT图像迭代重建算法

为解决探测器尺寸受限导致的CT图像重建区域面积受限以及X射线辐射剂量较大问题,提出一种半扇束扫描模式下的CT图像迭代重建算法。该算法将探测器水平偏置,稀疏角度下采集物体投影数据,利用ART-TV迭代算法对投影数据进行重建,达到预设迭代次数后,输出重建图像。实验结果表明:半扫描可扩大重建面积,降低探测器成本;利用迭代重建算法,降低剂量的同时重建优质CT图像。     

探测器分块排列的CT系统及其图像重建

为解决CT系统中扫描视野受限及低剂量成像问题,提出一种探测器分块排列的CT系统及其稀疏角度CT图像迭代重建方法。探测器分块排列可扩大CT图像物体扫描视野,稀疏角度采集投影数据能有效降低辐射剂量,同时采用ART-TV迭代算法重建CT图像。仿真实验表明:该方法可有效扩大CT系统扫描视野,在稀疏角度获取投影数据采集方式下,利用ART-TV迭代重建算法可重建优质CT图像,实现降低辐射剂量的目的。     

递变电压下投影融合图像重建研究

针对变电压投影数据中的不完全投影数据重建问题,提出基于投影数据线性融合的变电压CT重建算法。该算法根据最佳灰度带提取递变电压投影序列中的有效信息,利用线性融合的方法,把低电压下的投影数据通过线性关系融合到相邻高电压投影数据上,依此类推直至最高电压,获得一幅完整信息的高动态投影数据,并利用TV-ART算法重建。实验表明:线性融合算法不仅实现了变电压图像信息的完整重建,像素值也更加稳定。     

基于Wiener滤波的反投影图像重建算法

CT是一种先进的成像技术,投影重建图像为关键技术之一,目前CT图像重建算法多采用滤波反投影针对投影数据不足所产生伪影的问题,经分析伪影产生的原因后,提出了一种基于Wiener滤波与反投算法。算法利用Wiener滤波对传统的滤波反投影图像重建算法进行改影图像重建算法相结合的新图像重建算法,该克服重建图像伪影。通过对典型流型进行实验仿真,证明改进后的算法对重建图像的质量有明进,能较好地显改善。     

基于改进平滑硬阈值约束的CT迭代重建算法

稀疏角度投影数据重建CT图像,是一种有效的降低X射线辐射剂量的方式。提出一种改进的平滑硬阈值(SHT)约束,使其更接近于L_0范数,同时最优参数不受重建图像影响。该重建算法沿用ART-TV的重建策略,即对每次ART重建后的图像进行改进SHT的最小化约束。实验表明:新算法提高了重建图像质量,信噪比更高,平均绝对误差更小。     

基于小波阈值去噪的CT图像重建

实际扫描过程中投影数据不可避免地受到各种噪声的干扰,进而影响了图像重建的精度.提出了一种基于小波阈值去噪的图像重建方法,首先对不同角度下的投影数据进行小波分解,并对分解后的小波系数进行阀值化去噪处理,然后经过逆小波变换得到去噪后的投影数据,再由这些去噪后的投影数据进行图像重建.实验结果表明本文的方法非常有效,与传统的重建方法相比,由去噪处理后的投影数据所重建的图像质量明显改善.     

GPU梯度自适应SART图像重建算法

针对SART迭代重建算法所需投影数据量大且迭代时间长的问题,将TV算法引入SART中,动态调节梯度步长来加速算法的收敛性能,实现用少量投影数据重建出高质量的图像。为加快算法的执行速度,将SART-TV算法在GPU上并行加速。用SART算法和SART-TV算法对Shepp-Logan模型重建,仿真实验表明:在采样数据相同的情况下,SART-TV算法较SART算法可以重建出更好的图像,且基于GPU的SART-TV算法的迭代时间明显低于基于CPU的SART-TV算法。     

少投影钢管截面CT重建研究

通过钢管截面CT图像,可以获取其大部分的参数指标,全面检测钢管质量.但是CT图像重建往往需要大量投影数据,这些数据的采集和计算非常耗时.为了加快钢管检测的速度,本文研究了少投影条件下钢管截面的图像重建算法并通过模拟数据验证了其重建的效果.我们分别用ART、MAP和OSEM这三种迭代重建算法对仿真模型进行了重建试验,并根据钢管本身的先验知识分布对算法做了改进,使重建图像质量有了明显的改善.模拟试验的结果表明,ART、MAP和OSEM算法可以实现少于20组投影数据下钢管截面较为精确的重建,并且可以做到10组投影下的近似截面重建.     

OSEM算法在编码板成像中的应用

为提高γ辐射编码成像中MLEM算法在图像重建时的速度及质量,论文基于核医学ECT图像重建中的OSEM算法思想在图像重建时对编码成像所得投影数据进行分组,并采用精细采样平衡相关法的重建结果作为初值进行迭代。通过实验对该算法进行验证。实验表明:OSEM算法可以有效提高收敛速度,改善重建图像质量。在γ辐射编码成像中采用OSEM算法是有效且可行的。     

基于电子束扫描阵列微焦点射线源的倒置结构Micro-CT成像研究

倒置几何结构CT成像系统理论上具有扫描视场大、图像信噪比好、锥束伪影小等优点,但其多焦点、稀疏角的扫描模式亦会带来投影数据截断、稀疏和局部数据冗余等问题。本文利用电子束扫描阵列微焦点射线源和高分辨率小面积探测器等构建了一种新型高分辨率、大视场的倒置几何结构Micro CT实验系统(IG Micro CT)。针对该系统多焦点、稀疏角扫描模式下的投影数据截断和稀疏等特点,提出一种图像先验约束的全变分正则化SART迭代CT图像重建算法。首先通过仿真实验对图像重建算法进行了验证,并对阵列微焦点数量、旋转扫描分度数量等扫描参数进行优化,最后在IG Micro CT实验系统上获得了高分辨的Micro CT测试图像。实验结果表明,本文提出的算法适用于IG Micro CT系统,解决了投影数据截断、稀疏采样和局部数据冗余带来的条状等伪影问题,并验证了IG Micro CT这种新型成像方式的可行性。     

基于Chambolle-Pock算法的TV重建方法研究

为实现CT稀疏视角下的投影图像重建,Sidky等设计了基于Chambolle-Pock(CP)算法,论文在此基础上实现了CP算法。仿真实验表明,与传统的滤波反投影算法相比,CP算法不存在伪影,在含噪情况下,CP算法具有较好的性能,可以实现稀疏角度下的高精度图像重建。同时,探讨了平衡因子的选取对重建精度的影响。     

Hybrid reconstruction algorithm for computed tomography based on diagonal total variation

Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and rootmean-square error(RMSE) and structure similarity(SSIM)were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct highquality image from incomplete projection data.     

A complete implementation of list-mode reconstruction for PET

Tomography reconstruction algorithm is one of the key components of positron emission tomography (PET) scanners,most PET scanners use statistical iterative reconstruction algorithms from data in sinograms currently. However tomography reconstruction using list-mode data has many unique advantages,in recent years great attention has been paid to it,being in the process of rapid development and improvement.In this paper,using experimental data of small animal PET scanner Eplus-166,exploiting ordinary subsetized list-mode EM(S-LMEM) algorithm and orthogonal distance-based ray-tracer(OD-RT),we eventually achieve list-mode tomography reconstruction.System response matrix(SRM),which establishes mapping relationship between the image and the projection space,is one key problem in iterative reconstruction algorithm.OD-RT is based on an optimization Siddon’s algorithm to calculate the SRM,generating line-of-response(LOR) which is approximately Gaussian-shaped,achieving better modeling of detector response function(DRF).The results demonstrate that image resolution recovery achieves the inherent properties of the scanner and that on-the-fly ray-tracer for real-time calculation of system response matrix is feasible for dynamic reconstruction.Meanwhile,the optimal parameters for calculating SRM are found by experiments.     

A New Approach to the Fan Beam Geometry Image Reconstruction for a CT Scanner

A new derivation of the fan beam geometry image reconstruction formula for CT scanners has been made in this paper. Moreover there are two points discussed here in order to develop fast algorithms based upon this formula. First is to establish a principle of filterered back-projection algorithm for fan beam geometry which enables us to use FFT algorithm. Second is to develop a fast algorithm for fan back-projection process. With these algorithms, the fan beam image reconstruction time to compute can be made comparable with the filtered back-projection algorithm for the parallel beam geometry image reconstruction.     

中间函数法CT图像重建算法研究

CT自从被发明以来其技术已发生了很大的变化.这些变化不仅体现在计算机技术、探测器技术和X线技术方面,同时CT的图像重建算法也在不断地发展.本文提出的中间函数重建算法,是一种可以应用于扇束和锥束扫描的图像重建算法.研究它的目的是为将来的锥束扫描提供直接重建算法.     

A novel algorithm for transmission image reconstruction of tomographic gamma scaners

<正>It is difficult to develop image reconstruction algorithms for tomographic gamma scanning based on drummed radioactive residues or wastes.In this paper,a novel reconstruction algorithm of transmission image for tomographic gamma scanning is proposed.It is based on the conventional transmission equation and equivalent gamma-ray track length modified by a Monte Carlo method.The algorithm is implemented by simulating the samples on the established platform.For the verification experiments of the algorithm,several cubic voxel samples were designed and manufactured.Experimental tests were conducted.The tomographic gamma scanning of transmission images is compared with the linear attenuation coefficients by the simulated values and experimental data with the algorithm and the reference values.The results show that the absolute relative errors of the reconstructed images are less than 5%.     

Generalized flow pattern image reconstruction algorithm for electrical capacitance tomography

Successful applications of electrical capacitance tomography (ECT) depend on the speed and precision of the image reconstruction algorithms. In this paper, based on the semiparametric model, a generalized objective functional that considers the outliers in the measured capacitance data and the model error is proposed. A regularized combination minimax estimation is developed. An efficient algorithm, which integrates the advantages of the homotopy method where the homotopy equation is designed by the fixed-point homotopy and solved using the fixed-point iteration algorithm based on the alternate iteration scheme, the quantum particle swarm optimization algorithm that is coupled with the crossover and mutation operators, and the simulated annealing algorithm, is proposed. This algorithm is tested by the noise-free capacitance data and the noise-contaminated capacitance data, and encouraging results are observed. Numerical simulation results reveal the effectiveness and superiority of the proposed algorithm. In the cases of the reconstructed objects considered in this paper, the reconstructed results by the proposed algorithm show great improvement in the spatial resolution and accuracy. The spatial resolution of the reconstructed images is enhanced, and the artifacts in the reconstructed images can be removed effectively. Furthermore, the reconstructed results by the proposed algorithm under the noise-contaminated capacitance data reveal that the proposed algorithm is very competent to deal with the inaccurate nature in the capacitance data. Consequently, a promising algorithm is introduced for ECT image reconstruction.     

Compressed sensing and Otsu’s method based binary CT image reconstruction technique in non-destructive detection

This paper tries to address the problem of binary CT image reconstruction in non-destructive detection with an algorithm based on compressed sensing(CS) and Otsu's method, which could reconstruct binary CT image of test object from incomplete detection data. According to binary CT image characteristics, we employ Splitbregman method based on L1/2regularization to solve piecewise constant region reconstruction. To improve the reconstructed image quality from incomplete detection data, we utilize a priori knowledge and Otsu's method as the optimization constraint. In our study, we make numerical simulation to investigate our proposed method,and compare reconstructed results from different reconstruction methods. Finally, the experimental results demonstrate that the proposed method could effectively reduce noise and suppress artifacts, and reconstruct high-quality binary image from incomplete detection data.     

数字图象重建的一种综合快速算法

本文提出一种综合快速算法,可直接快速地计算重建图象平面上任何一点的检测角,并采用三次B样条函数对滤波的投影数据进行内插,来代替反投影时的内插。实验表明,在保证同样的主客观保真度下,此算法的内插计算量约为原来算法的1/12;当象素数N增大时,计算量的减少更为显著。对端点条件的影响进行了分析,证明用此法插值所造成的误差以相当高的速率由边缘向中心衰减,大约每向中心移动两个象素其误差减少一个数量级。