Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

The projection matrix model is used to describe the physical relationship between reconstructed object and projection.Such a model has a strong influence on projection and backprojection,two vital operations in iterative computed tomographic reconstruction.The distance-driven model(DDM) is a state-of-the-art technology that simulates forward and back projections.This model has a low computational complexity and a relatively high spatial resolution;however,it includes only a few methods in a parallel operation with a matched model scheme.This study introduces a fast and parallelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations.Our proposed model has been implemented on a GPU(graphic processing unit) platform and has achieved satisfactory computational efficiency with no approximation.The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop,respectively,with an image size of 256×256×256 and 360 projections with a size of 512×512.We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation.The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction.     

非精确交替方向总变分最小化重建算法

CT (computed tomography)系统实际应用当中, 经常会出现扫描数据不满足数据完备性条件的情况. 针对不完全角度重建问题的研究, 是目前迭代型算法研究中的一个热点. 一系列基于带有约束的总变分最小化的重建算法近年来在不完全角度重建中取得了较好的效果, 这其中基于交替方向法 (alternating direction method, ADM) 的重建算法表现出更好的性能. 然而, ADM方法在求解过程中对矩阵求逆的处理效率不高, 导致极大的计算开销. 本文针对该问题, 使用非精确ADM方法, 利用线性近似的方式替换掉计算开销较大的项, 使得矩阵求逆问题可以通过快速傅里叶变换加速实现. 实验结果表明, 本文提出的非精确交替方向总变分最小化重建算法与精确ADM重建算法相比, 没有明显的精度损失, 计算时间缩减30%左右. 关键词： 不完全角度重建 总变分最小化 非精确交替方向法     

基于稀疏优化的计算机断层成像图像不完全角度重建综述

计算机断层成像(computed tomography,CT)技术在医学和工业无损检测中都具有非常广泛的应用,CT重建算法是其中的核心,而不完全角度重建问题则是实际应用中重建算法研究领域的一个热点和难点问题.近年来,随着稀疏优化理论与算法的飞速发展,基于稀疏优化的重建算法已经在不完全角度重建问题中得到了较广泛的应用,且表现出了良好的精度与速度性能.本文首先对稀疏优化的基本理论结论与常用算法进行了介绍;而后对稀疏优化理论在CT图像不完全角度重建中的应用进行归纳,分类介绍了其主要研究成果及稀疏优化所发挥的作用;最后对基于稀疏优化的不完全角度重建研究进行了展望.     

Optimization-based image reconstruction in x-ray computed tomography by sparsity exploitation of local continuity and nonlocal spatial self-similarity

The additional sparse prior of images has been the subject of much research in problems of sparse-view computed tomography(CT) reconstruction. A method employing the image gradient sparsity is often used to reduce the sampling rate and is shown to remove the unwanted artifacts while preserve sharp edges, but may cause blocky or patchy artifacts.To eliminate this drawback, we propose a novel sparsity exploitation-based model for CT image reconstruction. In the presented model, the sparse representation and sparsity exploitation of both gradient and nonlocal gradient are investigated.The new model is shown to offer the potential for better results by introducing a similarity prior information of the image structure. Then, an effective alternating direction minimization algorithm is developed to optimize the objective function with a robust convergence result. Qualitative and quantitative evaluations have been carried out both on the simulation and real data in terms of accuracy and resolution properties. The results indicate that the proposed method can be applied for achieving better image-quality potential with the theoretically expected detailed feature preservation.     

Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

Linear scan computed tomography (LCT) is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation (TV) minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method (ADM) to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.     

Novel Fourier-based iterative reconstruction for sparse fan projection using alternating direction total variation minimization

Sparse-view x-ray computed tomography(CT) imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform(NUFFT) is presented in this work along with advanced total variation(TV) regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively.     

Cu掺杂对ZnO基薄膜光学及磁学性能影响

本文采用脉冲激光沉积(PLD)方法在单晶Si(100)衬底上沿c轴方向生长出单晶ZnCoAlO薄膜,并通过加镀Cu层调节薄膜的光学和磁学特性.采用X射线衍射仪(XRD),光致发光光谱仪,振动样品磁强计(VSM)和霍尔效应仪对薄膜的结构、光学和磁学性能进行了研究.实验表明,样品均具有纤锌矿结构并沿(002)面择优生长.加镀Cu层之后,薄膜紫外发光得到增强,掺杂导致薄膜ZnO晶格能带间隙变宽,并使得近带边激子发光增强.同时发现,在室温下Cu离子对薄膜磁性和电子浓度产生影响,Cu掺杂可以改变薄膜中载流子浓度,并影响原有磁性的双交换机理.     

水热法辅助溶胶-凝胶法制备Al∶ZnO纳米棒阵列及发光性能研究

采用水热法结合溶胶-凝胶法在SiO2基片上制备了不同Al含量掺杂的ZnO纳米棒阵列.通过X射线衍射仪(XRD),电子扫描显微镜(SEM),透射光谱和光致发光光谱仪(PL)等测量手段,分析了Zn1-xAlxO薄膜样品的微结构、表面形貌、透射及光致发光特性.结果表明,制备出的Zn1-xAlxO薄膜具有良好的结晶质量和明显的沿(002)方向择优取向生长.透射谱分析显示,样品的吸收边随Al含量的增加出现明显的红移现象.PL谱分析表明,掺杂Al以后,薄膜出现强的橙红光发射光谱带,通过谱线拟合,发现在可见光波段的缺陷发光主要是位于能量为1.92eV和2.15 eV的红光及黄光发射,主要发光机理为Zn,缺陷发射.     

Mg掺杂对ZnO薄膜结构与磁性的影响

采用脉冲激光沉积(PLD)方法在单晶Si(100)衬底上制备Zn1-xMgxO薄膜,研究了退火温度和氧压对Zn1-xMgxO薄膜的结构和磁性的影响.结果表明,Mg掺入量影响ZnO结构相变,当x≥0.25时,Zn1-xMgxO薄膜由六角纤锌矿结构变为立方结构,同时磁性增强.随着氧压的增大和后续退火温度的升高,都会使饱和磁化强度(Ms)呈先增大后减小的趋势.分析表明磁性的变化都与样品中的表面缺陷浓度有关.