燃油喷雾内部构造可视化的激光CT技术(1)——喷雾图象重建方法的研究

为应用激光CT(Computed Tomography)技术实现燃油喷雾内部构造可视化,本文针对燃油喷雾的特点,对卷积反投影法(Convolution back projection简称CBP)、代数重建技术(Algebraic reconstruction technique简称ART)和同时迭代重建技术(Simultaneous iterative reconstruction technique简称SIRT)三种算法应用于喷雾图象的重建进行了研究.在P540图象处理系统上对标准喷雾模型进行重建,结果表明在投影数据存在噪声时,SIRT法重建图象质量最佳,但所需时间最长,CBP法重建图象质量最差,但运算时间最少,而ART法介于两者之间.     

复杂流场的代数迭代重建算法

提出了简单自相关代数迭代重建算法（SSART）。采用数值模拟的方法,对当前有代表性的基本代数迭代法（ART）、联合代数迭代法（SART）、改进的联合代数迭代法（MSART）以及SSART进行了计算模拟,对比分析了各种算法的模拟效果和重建精度。结果发现,SSART的均方误差（MSE）在10^-4数量级,比ART的降低了78．2％;峰值相对误差（PE）在10^-2,降低了92．9％;计算程序上,SSART仅比ART多1个除数因子。所以SSART具有算法简单、重建精度高、稳定性好和自愈能力强等优点。     

广播与电视

为了克服传统的少射线图像重建方法一ART对噪声敏感而导致的重建图像质量差的问题,在考虑气体扩散时其浓度二维分布特点的基础上,提出了一种利用多目标优化的方法来重建气体二维浓度分布图的方法。实验表明,该算法对改善气体浓度层析成像中的噪声对重建结果的影响具有较好的效果。     

一种改进的离散代数重建算法(DART)

医学CT中的图像往往由几种已知的灰度值组成,利用这些先验知识可降低重建条件提高图像重建质量。因此提出一种基于联立迭代算法(SIRT)的离散代数重建算法(DART),并且通过实验实现了在少数投影数目和小角度范围下的图像重建,并与其他几种传统的重建算法进行了比较,结果显示DART能从更少的投影数据下更精确地重建出图像同时有效地抑制了噪声。     

ART算法的平均值法改进方案

二维断层成像中,代数重建(ART)算法面临的最大问题就在于计算量大、重建速度慢。针对这个劣势,提出了一种使用平均值法改进的ART算法,希望能更快地重建出质量较好的图像。该算法将每一次迭代过程的所有中间值记录下来,并求出其平均值,将此平均值作为下一次迭代的初始值。经过实验证明这种改进后的ART算法经过更少的迭代次数后就能达到较好的重建质量,且质量比传统算法还要好。     

基于TDLAS的二维温度场重建算法

可调谐半导体激光吸收光谱(TDLAS)技术结合层析成像(CT)算法能实现流场温度、浓度等信息的二维重建测量。为研究层析成像算法对温度场二维重建质量的影响,实现了两种典型重建算法:代数迭代重建算法(ART)和模拟退火(SA)算法。在不同的射线分布和吸收谱线数目情况下,使用两种算法对给定单峰温度场和双峰温度场分别进行重建仿真,比较分析了两种算法的重建结果。仿真结果表明,影响代数迭代重建算法重建质量的主要因素是射线分布,而模拟退火算法则对吸收谱线数较为敏感;对于单峰温度场,代数迭代重建算法重建结果的最大偏差为5.6%,略好于使用6条吸收谱线时模拟退火算法重建结果的6.2%;对于双峰温度场,模拟退火算法重建结果的最大偏差为5.5%,而代数迭代重建算法的最大偏差则高达22%。     

双极场逆Radon变换的数值模拟

对双极场（DPF）的逆Radon变换进行了数值模拟。采用加法代数重建迭代算法（ART）对含有正负值的DPF进行重建，迭代了500次。结果发现，迭代一直收敛，重建场与原场相似，包括峰的位置、方向和形状，但各个峰的高度都较原场相应的峰矮，重建区域的边界出现了明显的波动现象。与相应单极场（SPF）的重建误差作比较，结果发现，DPF的3种模拟误差都大于SPF相应的误差，其中均方误差（MSE）大10^-4数量级，绝对平均误差（AVE）、峰值相对误差（PE）分别大10^-3、10^-2数量级，说明同样条件下DPF的重建精度比SPF的小。     

基于有限角图像重建的两种迭代算法研究

针对有限角度投影数据的CT图像重建问题,本文介绍了两种迭代算法,其中主要介绍了基于最小化图像总变差的优化准则的迭代重建算法--TV算法,以及简单介绍了改进后的ART算法,该算法的基本思想是运用已知角度的投影数据来补全未知角度的投影数据,再用ART算法进行图像重建.最后用模拟的有限角度投影数据分别对这两种迭代算法进行了图...     

基于多水平系统的锥束ART算法

代数重建技术(ART)是X-射线CT图像重建的一种重要迭代算法,投影的访问顺序对其收敛速度有重要影响。1994年,Guan和Gordon提出了多水平访问系统(MLS),该系统在投影数为2的整数次幂时效果最好。针对MLS仅适用于[0,π)上的均匀投影的问题,将MLS推广到[0,2π)上,在特定的投影数情形下,分析投影数特点,提出了三等分方法,该方法对对称投影访问顺序进行了改进。仿真实验结果表明,推广后的两系统下的锥束ART算法在迭代中收敛速度都要快于随机访问系统(RAS)和顺序访问系统(SAS)下的锥束ART算法。     

自相关代数迭代重建算法重建含遮挡物场

用自创建的简单白相关代数迭代重建算法（SSCART）重建含遮挡物场，分析了重建效果。采用数值模拟的方法，分别用原始的代数迭代重建算法（ART）与SSCART重建含遮挡物场，分析了模拟效果和重建精度。结果发现，这2种算法都能重建含建遮挡物场，但重建效果差别较大，SSCART能较精确重建原场。SSCART算法的重建精度MSE指标在10^-4数量级上比ART的降低了26．6％，PE指标在10^-2降低了77．6％。     

微粒直径及直径分布的激光测量技术

本文较全面地介绍了微粒直径及直径分布的激光测量技术.详细讨论了光全散射法、光角散射法、衍射法及激光脉冲全息法的测量原理、适用范围及其发展.研究结果表明,光学法测粒具有测量粒度范围广、重复性好、精度高、不接触样品、不要求导电介质以及测量时间短并可在线实时测量等优点.     

电容层析成像图像重建算法对比

图像重建算法在电容层析成像技术的实际应用中起着至关重要的作用。针对图像重建算法的研究,文中将线性反投影法、奇异值分解法、代数重建算法、Landweber算法、Tikhonov正则化算法的基本原理进行对比。基于MATLAB仿真平台对4种多相流流型进行仿真,并从图像误差、相关系数、计算时间3个方面对比重建图像的效果。分析结果表明,直接算法的图像重建速度优于迭代算法,但其图像重建质量劣于迭代算法。     

Improved tomographic reconstruction in seven-pinhole imaging

Cardiac emission tomography using a seven-pinhole collimator has received only little appreciation as a diagnostic imaging technique. The main reasons are the limited angular sampling of the seven-pinhole device and the difficulties encountered in properly positioning the patient relative to the collimator/camera system. In order to overcome these problems, we have developed a modified ART3 algorithm for reconstruction of the radioactivity distribution in the heart. The method is very appropriate for seven-pinhole tomography, as demonstrated by the quality of the reconstructions, by the excellent point source resolution of the system response, and by a comparison to two other suitable reconstruction techniques, viz., SMART and SIRT.     

Reconstructing non-ideal-bordered field by simple self-correlative algebraic reconstruction technique

A new algorithm for iterative reconstruction is suggested. It is named simple self-correlative algebraic reconstruction technique （SSART）. With numerical simulation experiments, SSART was applied in reconstructing a non-ideal-bordered field in order to test its reconstructive effect, For contrast, three current representative algebraic reconstruction（ARTs） including basic ART, simultaneous ART （SART） and modified SART （MSART） were simulated simultaneously. The calculated results and reconstructive accuracy are discussed with three kinds of error indexes, namely mean-square error （MSE）, absolute value error （AVE） and peak error （PE）. As the results, the indexes of reconstructive accuracy are much improved by the proposed SSART. The MSE and PE have been decreased by 63.6% on the order of magnitude 10-4 and 88.9% on the order of magnitude 0-2,respectively,compared to that of ART. It is concluded that SSART is one of the most super iterative reconstructing techniques.     

Emission Spectral Tomography Reconstruction Based on Maximum Entropy Interpolation

To improve the performance of optical computed tomography (OpCT) reconstruction in the case of limited projection views, maximum entropy (ME) algorithms were proposed and can achieve better results than traditional ones. However, in the discrete iterative process of ME, the variables of the iterative function are continuous. Hence, interpolation methods ought to be used to improve the precision of the iterative function values. Here, a sinc function interpolation approach was adopted in ME algorithm (SINCME) and its reconstruction results for OpCT with limited views were studied using four typical phantoms. Compared results with ME without interpolation, traditional medical CT back-projection algorithm (BP), and iterative algorithm algebraic reconstruction technique (ART) showed that the SINCME algorithm achieved the best reconstruction results. In an experiment of emission spectral tomography reconstruction, SINCME was also adopted to calculate the three-dimensional distribution of physical parameters of a candle flame. The studies of both algorithm and experiment demonstrated that SINCME met the demand of limited-view OpCT reconstruction.     

Improved iterative image reconstruction with automatic noise artifact suppression

A method for stabilizing iterative image reconstruction techniques has been developed for improving the image quality of position emission tomography. A damping matrix is introduced, which suppresses noisy correction on a pixel-by-pixel basis, depending on the statistical precision of the iterative correction. The precision is evaluated by comparing a certain number of correction submatrices, each of which is formed from a subset of the projection data. Simulation studies showed that statistical noise is effectively suppressed, while the image of the source object is reconstructed with high resolution, as long as the signal level is higher than the local noise level. In the application to the MLE (maximum likelihood estimator), the minimum RMS error of the image was reduced to 84% for 500 k total counts, and the RMS error increased more slowly with further iterations as compared with the simple MLE. The method was also applied to the FIR (filtered iterative reconstruction) algorithm, and the images were found to be better than those obtained by the convolution backprojection method.     

Constrained iterative reconstruction by the conjugate gradient method

The conjugate gradient method incorporating the object-extent constraint is applied to image reconstruction of a three-dimensional object using an incomplete projection-data set. The missing information is recovered by constraining the solution with the knowledge of the outer boundary of the object-extent which may be a priori measured or known. The algorithm is derived from the least-squares criterion as an advanced version of conventional iterative reconstruction algorithms such as SIRT (Simultaneous Iterative Reconstruction Technique) and ILST (Iterative Least Squares Technique). In the case of reconstruction from noisy projection data, a method based on the minimum mean-square error criterion is also proposed. Computer simulated reconstruction images of a phantom using limited angle and number of views are presented. The result shows that the conjugate gradient method incorporating the object-extent constraining provides the fastest convergence and the least error.     

Computational analysis and improvement of SIRT

Iterative X-ray computed tomography (CT) algorithms have the potential for producing high-quality images but are computationally very demanding, especially when applied to high-resolution problems. Focusing on simultaneous iterative reconstruction technique (SIRT), we provide an eigenvalue based scheme for automatically determining a near-optimal value of the relaxation parameter. This accelerates the convergence rate of SIRT to the point where only half the number of iterations normally required is needed. We also modify the way SIRT uses preconditioning to solve a weighted least squares problem. The resulting algorithm, which we call PSIRT, is associated with a smaller memory footprint and calls for less data to be communicated in a distributed-memory implementation. Experimental residual norm and timing results are provided based on cone-beam micro-CT mouse data, including for an ordered subsets study.      

自适应稀疏度的1 bit压缩重构算法

1 bit压缩感知技术日益受到关注.1 bit信号往往有符号跳变,同时信号重构还需要稀疏度先验信息,如何有效地克服信号重构对稀疏度的依赖性,提高重构算法对噪声的鲁棒性,这是该领域面临的重大挑战.本文在二进制迭代硬阈值算法基础上,引入自适应稀疏度,利用残差能量的大小,通过对信号和噪声的学习,解决稀疏度依赖问题,通过引入弹...