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。     

Performance evaluation of the backprojection filtered （BPF） algorithm in circular fan-beam and cone-beam CT

In this article we introduce an exact backprojection filtered （BPF） type reconstruction algorithm for cone-beam scans based on Zou and Pan＇s work. The algorithm can reconstruct images using only the projection data passing through the parallel PI-line segments in reduced scans. Computer simulations and practical experiments are carded out to evaluate this algorithm. The BPF algorithm has a higher computational efficiency than the famous FDK algorithm. The BPF algorithm is evaluated using the practical CT projection data on a 450 keV X-ray CT system with a flat-panel detector （FPD）. From the practical experiments, we get the spatial resolution of this CT system. The algorithm could achieve the spatial resolution of 2.4 lp/mm and satisfies the practical applications in industrial CT inspection.     

基于硬件实现的锥束CT图像重建系统的存储机制设计

为了实现三维锥束CT图像重建加速系统的小型化,建立了基于FPGA的三维图像重建系统。并对该系统中所采用的FDK重建算法所需的数据存储量和数据传输量以及由SDRAM、SRAM和FPGA内部缓存组成的存储系统的数据吞吐率进行了研究。首先,根据FDK算法的滤波与反投影两个步骤介绍了三维锥束CT图像重建系统的数据规模。接着,介绍了一种以SDRAM为外部主存,以SRAM为外部缓存和以FPGA内部SRAM资源作为内部高速缓存的存储机制。然后,介绍了该存储机制的实现方法以及测试方法。最后对该三维图像重建系统的数据吞吐能力进行了测试,并将之与FDK算法所需的数据传输量进行了对比分析。试验结果表明:该存储机制的数据连续存取速度为151.9MB/s,数据随机存取速度为100MB/s,基本满足小规模的三维图像重建的数据存储与传输带宽的要求。     

基于基图像TV模型的CT射束硬化校正方法

X射线CT中,X射束硬化导致重建图像中出现伪影,严重影响了图像质量。论文深入分析了射束硬化对原始投影数据的影响,并提出了一种基于基图像TV模型的射束硬化校正方法。该方法首先依据射束硬化的物理特征建立了带有可调参数的初步校正模型;其次,在不同的可调参数条件下,原始投影数据经该模型预处理变换得到多组预处理投影序列;再次,分别对预处理投影序列进行重建得到一系列校正基图像;最后,将基图像的线性组合作为最终重建图像。其中,加权系数的最优解是以最终重建图像的全变分(Total Variation,TV)函数作为目标函数,通过迭代法求得。为验证该算法,对真实的铝柱体模和工业检测件进行了实验,结果表明,该算法对射束硬化引起的杯状和条状伪影均有显著的抑制效果。     

Three-dimensional weighting reconstruction algorithm for circular cone-beam CT under large scan angles

Improving imaging quality of cone-beam CT under large cone angle scan has been an important area of CT imaging research. Considering the idea of conjugate rays and making up missing data, we propose a three-dimensional(3D) weighting reconstruction algorithm for cone-beam CT. The 3D weighting function is added in the back-projection process to reduce the axial density drop and improve the accuracy of FDK algorithm. Having a simple structure, the algorithm can be implemented easily without rebinning the native cone-beam data into coneparallel beam data. Performance of the algorithm is evaluated using two computer simulations and a real industrial component, and the results show that the algorithm achieves better performance in reduction of axial intensity drop artifacts and has a wide range of application.     

基于异构多GPU的锥束CT图像重建研究

针对锥束CT图像重建系统中GPU型号不一致问题,提出了基于异构多GPU的重建模型。该模型基于FDK算法进行重建,采用了按计算能力进行任务分配的方法,确保各GPU计算平衡。采用数据流分解的方法,实现了海量数据的图像重建。给出了该重建模型基于CUDA的实现方法,包括采用流管理和异步函数来实现多GPU并行计算以及滤波和反投影核函数的流程设计。利用高精度工业CT系统进行模型的实验验证。结果表明：所建立的重建模型正确有效,能充分发挥系统中异构多GPU的计算能力,执行效率高。     

基于SART算法的CL硬化伪影校正方法研究

X射线薄板层析成像(CL)系统是一种针对板状构件的新型断层成像系统,该系统中存在射束硬化现象。本工作研究了一种基于SART算法的硬化伪影校正算法（SART-BHC算法）,通过对该算法的研究及对CL系统矩阵的计算,使该方法能应用于CL中。通过模拟与实验相结合的方式,利用蒙特卡罗方法获得CL投影的模拟数据,在实际CL中获得实验数据,然后利用SART-BHC与FPB算法对两种数据分别重建。结果表明,SART-BHC算法可应用于CL中,不需要任何先验知识,能很好地校正硬化伪影,并对层间混叠有抑制作用。     

Slice-wise reconstruction for low-dose cone-beam CT using a deep residual convolutional neural network

Because of the growing concern over the radiation dose delivered to patients, X-ray cone-beam CT(CBCT) imaging of low dose is of great interest. It is difficult for traditional reconstruction methods such as Feldkamp to reduce noise and keep resolution at low doses. A typical method to solve this problem is using optimizationbased methods with careful modeling of physics and additional constraints. However, it is computationally expensive and very time-consuming to reach an optimal solution. Recently, some pioneering work applying deep neural networks had some success in characterizing and removing artifacts from a low-dose data set. In this study,we incorporate imaging physics for a cone-beam CT into a residual convolutional neural network and propose a new end-to-end deep learning-based method for slice-wise reconstruction. By transferring 3D projection to a 2D problem with a noise reduction property, we can not only obtain reconstructions of high image quality, but also lower the computational complexity. The proposed network is composed of three serially connected sub-networks: a cone-to-fan transformation sub-network, a 2D analytical inversion sub-network, and an image refinement sub-network. This provides a comprehensive solution for end-to-end reconstruction for CBCT. The advantages of our method are that the network can simplify a 3D reconstruction problem to a 2D slice-wise reconstruction problem and can complete reconstruction in an end-to-end manner with the system matrix integrated into the network design. Furthermore, reconstruction can be less computationally expensive and easily parallelizable compared with iterative reconstruction methods.     

Constrained Optimization Algorithms for Divergent Ray Tomography

Using the projections as constraints, the reconstruction of an object from its fan beam projections is formulated and solved as a problem in constrained optimization. First a general cost criterion is optimized and the result is applied to several specific criteria. This produces a number of relationships (models) between the image and the Lagrange multipliers introduced by the Euler-Lagrange method. Utilizing these models, the ART methods are extended to fan beam projections. A non-recursive algorithm which exploits the speed of the block fast Fourier transform is given and compared with an existing convolution algorithm. The projection slice theorem for divergent ray geometry is given by introducing a new transform, the Angular Projection Transform.     

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.     

锥束CT重建FDK算法的两级并行计算研究

三维锥束CT图像的FDK算法重建由于运算量大,在重建高分辨率的图像时,重建所需时间通常难以满足实际应用的需求,集群并行计算是解决上述问题的常用方法之一.在一个SMP集群系统上,采用MPI和Pthreads两种模型相结合的方法,通过节点之间的消息传递和节点内部的共享内存,实现了FDK算法的两级并行.     

基于Radon变换导数的精确三维CT图像重建理论与改进方法介绍

本文主要介绍了一种基于Ｒａｄｏｎ变换导数的精确３Ｄ－ＣＴ图像重建的改进方法，它的计算复杂性和成像质量与传统方法相比有很大改善。     

Tomographic Algorithms for General Line Integrals

This paper extends the constrained optimization image reconstruction techniques to curved-ray projections for a number of scanning systems and for 2-D and 3-D reconstructions. Teh treatment presented is general in that it includes the previous results on parallel-ray and divergent-ray geometries as special casss. Employing the projection data as constraints, the reconstruction problem is expressed as a generalized constrained optimization problem whose solution leads to a relationship (model) between the reconstruction and the associate Lagrange multiplier functions, thus introducting the models for a number of prescribed cost criteria and scanning systems involing curved-ray projections. Using these new models a category of subspaces of a Hirbert space, the elements of which are the functions (objects) for reconstruction, is presented. The projections and the minimum energy reconstruction are shown to be projections of the object into these new subspaces. The projection slice theorem is extended by introducing a new transform, a slice of which is equal to the Fourier series of the corresponding projection, irrespective of the projection geometry. The ART methods are extended to curved-ray scanning systems. Also a convergent iterative algorithms which evaluates the Lagrange multipliers from general line integrals and then calculates the reconstruction, is introduced. The iterations of this algorithm are identical to those of the additive ART, thus resulting in the same solution.     

A fully three-dimensional reconstruction algorithm with thenonstationary filter for improved single-orbit cone beam SPECT

Conventional single-orbit cone beam tomography suffers from incomplete sampling and an inadequate three-dimensional (3D) reconstruction algorithm. The commonly used Feldkamp reconstruction algorithm simply extends the two-dimensional (2D) fan beam algorithm to 3D cone beam geometry. A truly 3D reconstruction formulation based on the 3D Fourier slice theorem is derived for a single-orbit cone beam SPECT. In the formulation, a nonstationary filter which depends on the distance from the central plane of the cone beam is derived and applied to the 2D projection data in directions along and normal to the axis of rotation. This algorithm was evaluated using both computer simulation and experimental measurements. Significant improvement in image quality was demonstrated in terms of decreased artifacts and distortions in cone beam reconstructed images. However, compared with the Feldkamp algorithm, a fivefold increase in processing time is required     

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.     

三投影CT钢管截面的二值图像重建研究

尺寸检测是保证钢管质量的重要环节,相关在线快速检测技术是目前钢管生产中亟待解决的技术难题。射线CT成像技术作为一种高效图像检测手段,能通过重建钢管截面图像获取钢管的大部分尺寸参数,特别适合对钢管质量进行检测和控制。为减少检测时间,实现钢管尺寸的在线检测和控制,本工作研究采用多源多探测器的CT扫描方式,实现了投影数据的快速获取,并根据钢管截面空间域和像素域的特点,对最大后验概率(MAP)图像重建算法进行了修正,实现了不完全投影数据条件下截面图像的重建。模拟试验的结果表明,修正后的MAP算法可做到最少3组投影下的钢管截面图像重建,得到的尺寸精度基本满足国家标准的要求,这一方法具有一定的理论和实际意义。     

螺旋CT三种近似方法重建效果研究

针对螺旋CT的三种近似重建算法FDK、Short-Scan FDK和PI-ORIGINAL,在相对螺距逐渐增大过程中的重建效果作了比较。仿真实验结果表明,在螺距较大的情况下,相对其他两种方法,PI-ORIGINAL方法优势明显。采用的仿真实验模型为3-D Shepp模型和Turbell＇s Cloclg型。     

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.     

PHASE CORRECTION AND BAND-PASS FILTERS IN CT IMAGING

This paper reports the use of the fast Fourier transform (FFT) in the direct Fourier transform method (DFM) in Computerized Tomography (CT) reconstruction. Phase corrections are needed in the CT reconstruction. In order to eliminate the image distortion from the basic DFM, Padding and band-pass filters are used in the improved DFM. Finally, some reconstructions from simulated projections and several experimental results are given.     

CT image correction for beam hardening using simulated projectiondata

A general beam-hardening correction technique is presented. Knowledge of the CT (computerized tomography) scanner X-ray spectrum is necessary. This postreconstruction method does not require the original projection data. Simulated projections through an uncorrected reconstructed image are used to correct for beam hardening. Errors in the mean linear attenuation coefficient are decreased from 30% to 5% with virtual elimination of the visual streaking artifact. The theoretical image improvement equals that of projection linearization postreconstruction methods using the original projection data. The correction is limited to cases where the material causing the beam hardening is contained within the reconstruction space