一种新的二维CT扫描方式及其重建算法

介绍了一种二维CT扫描方式及其重建算法。它是一种利用近轴X光线,针对大型回转试件的二维CT检测方法。被扫描试件依次绕与探测器平行的多个旋转中心各旋转一周。在旋转过程中,射线源在周向均布的多个角位置发射射线,同时探测器接收射线并记录投影数据。同传统的二代CT相比,对一个具体例子的计算表明,它可以节约3/4的扫描时间。计算机仿真表明了这种扫描方式和重建算法的可行性。     

锥束射线RT扫描大视场三维CT成像方法研究

受探测器尺寸和重建锥角的限制,基于单圆轨道扫描和FDK算法的三维CT成像方法难以对大物体进行三维CT成像。提出了一种基于平板探测器,采用锥束RT扫描方式的成像方法,推导了其三维CT成像算法。首先把对回转物体进行三次锥束平移透照的投影数据重新排成为更大范围的倾斜平行投影数据,然后经过加权滤波和反投影重建,获得物体的三维层析结果。仿真结果表明,该方法在重构大物体图像时,获得了满意的图像质量。水平方向视场是单圆轨道FDK算法视场的2.88倍,在垂直方向减少了锥角过大形成的伪影,提高了物体的重构精度。     

基于太赫兹量子级联激光器的反射式快速扫描成像

以太赫兹(THz)量子级联激光器为光源、低温热辐射计为信号接收端,采用可旋转和平移的二维扫描平台搭建反射式快速扫描成像系统。通过计算机控制扫描平台进行连续的旋转与平移运动,实时获取探测信号强度和样品位置信息,成功实现对直径为80mm圆形区域的快速扫描成像,扫描时间为5s,图像的平均空间分辨率约为1mm,系统成像时间大幅缩短。此外,成像装置中基于THz分束片的共光路设计,可有效减少系统光路元件,进一步缩小成像系统的体积。     

硬化伪影的新型表现形式及其校正

X射线硬化是导致工业CT重建图像质量下降的物理原因之一。硬化伪影通常表现为两种形式,即杯状伪影和带状伪影。描述并证实了硬化伪影的一种新型表现形式,这种伪影与真实结构相关,且分布规则,容易造成伪影与真实结构的混淆。采用线性化校正方法对该伪影进行抑制,提高了重建图像质量,改善了通过CT重建图像进行几何测量的精度。     

基于CT扫描数据的X射线能谱估计方法

X射线能谱在计算机层析成像(computed tomography,CT)图像硬化校正、双能谱CT成像、辐射剂量计算等方面具有重要作用.常用的估计X射线能谱分布的方法,利用X射线穿过不同厚度模体的衰减数据,来间接估计X射线能谱分布.由于该问题具有严重的病态性,因此如何鲁棒和准确地求解是能谱估计问题的关键.本文提出了一种利用CT扫描数据来估计X射线能谱分布的方法.该方法中考虑了谱估计和图像重建之间的相互印证关系,即谱估计正确时重建的CT图像无硬化伪影,而重建图像无硬化伪影时,则说明估计的谱准确.该方法利用这种相互印证关系构造优化模型,通过交替迭代求解,估计能谱分布和重建无硬化伪影的CT图像.数值实验和实际实验结果表明,该方法可以准确、鲁棒地估计出X射线能谱.     

不闭合CT扫描数据几何伪影的校正方法

针对扇束计算机层析成像(CT)不闭合的扫描数据,提出一种基于非线性优化模型的CT几何伪影校正方法。该方法对标志物细丝与被测物体同时扫描,通过求解基于细丝断层投影数据的非线性优化模型,精确估计CT系统的所有几何参数,进而校正包括扫描数据不闭合等几何参数误差引起的CT图像伪影。仿真和实测数据验证结果表明,利用本方法可有效消除不闭合扫描数据引起的CT图像几何伪影。     

利用CAD模型的不完全扫描CT图像重建

工业计算机断层成像(CT)扫描大尺寸和高密度工件时,会出现穿不透、扫描角度有限导致的投影数据不完备、重建伪影严重等问题。基于此,提出一种将工件的CAD设计模型作为先验知识,来实现该类对象的有限角CT重建优质图像的方法。由工件CT扫描的断层位置计算CAD模型对应的分层位置,并得到模型的像素截面;根据CT系统X射线能量和模型中各部分材质,确定和生成一幅衰减系数图像,并将其配准到一幅零灰度图像中,得到先验图像;最后对扫描投影数据进行SART+TVM+PRIOR算法重建,得到重建图像。仿真实验和实际工件扫描实验的结果显示,加入先验图像后重建的图像质量要远远优于未加入先验图像的重建结果,边缘结构更加清晰,并极大地减少了伪影。     

锥束CT系统旋转平移轨迹几何参数标定方法

针对锥束CT系统旋转平移（RT）轨迹中几何参数难以直接测量的问题,在单圆轨迹标定方法的基础上,提出了一种适用于RT轨迹的几何参数标定方法。该方法利用定标体模投影轨迹的椭圆参数与系统几何参数建立关系,解析求解出系统的内部参数。在此基础上,外推得到旋转轴所有的位置参数,并求得符合理想轨迹要求的几何参数。所求参数都可以通过解析的公式得到,能有效避免迭代法陷入局部最优的问题。对存在偏差的系统进行了仿真,并利用该方法进行标定,实验结果表明,该方法能有效抑制由于几何参数误差造成的几何伪影,提高图像质量。     

高压电缆源平移扫描CT高效重建算法EI北大核心CSCD

为提高在役高压电缆X射线扫描图像重建速度,结合传统的滤波反投影算法,提出基于数据平滑的局部扫描重建算法。分析了源直线扫描局部计算机断层成像方法存在的有限角和数据截断问题,提出数据平滑方式解决方法。主要途径是利用余弦函数沿探测器方向和射线源方向分别进行数据平滑插值,避免投影数据值在这两个方向上突然降为零,起到抑制截断伪影和有限角伪影的作用。实验证明,所提方法能有效抑制图像伪影,有利于电缆阻水缓冲层缺陷识别。相较于原有的联合迭代重建算法,该方法缩短了重建时间且图像重建质量相当;相较于传统滤波反投影算法,重建图像质量提高但重建耗时基本一致。     

考虑旋转中心标定误差的中子偏置计算机断层扫描成像方法

中子偏置CT(computed tomography)扫描是一种有效的大尺寸样品层析检测方法,但投影数据截断会导致较大的CT系统转台旋转中心标定误差,严重影响成像质量。基于投影数据对称性原理,提出了一种计算旋转中心左侧和右侧投影数据和之间方差的偏置CT扫描旋转中心精确标定算法。设计了对称补数据重建算法和投影数据预处理重建算法,验证得到,对称补数据重建算法对旋转中心标定误差更为敏感,较小的误差值会导致补齐后投影数据出现拼接缝以及拼接错位问题。提出了一种中子投影数据噪声仿真方法,设计的三维仿真模体验证了所提标定算法与投影数据预处理重建算法在不同旋转中心偏置大小以及不同强度投影噪声条件下的性能优势。基于反应堆中子源开展了中子偏置CT扫描成像验证实验,获得了样品清晰的内外部结构细节,中子CT成像系统的成像视野扩大了31.4%。     

改进的大锥角锥束CT圆轨迹反投影滤波算法北大核心CSCD

锥束CT圆轨迹反投影滤波(BPF)算法能够有效处理数据截断问题,在感兴趣区域成像研究中具有重要的地位。但是当锥角增大时,重建图像的顶端和底端会出现严重的伪影,从而影响图像质量。为解决该问题,从扇束圆轨迹BPF算法出发,重新推导了锥束圆轨迹BPF算法,通过对锥束伪影成因分析,提出了一种基于锥角大小和轴向距离大小的权重函数,修正了重建过程中差分反投影图像求解部分,达到抑制伪影的目的。实验结果表明,改进的大锥角锥束CT圆轨迹BPF算法能够在锥角增大时有效地抑制锥角效应,提高重建图像质量。     

Optimizing Image Reconstruction in SENSE Using GPU

Parallel magnetic resonance imaging (MRI) (pMRI) uses multiple receiver coils to reduce the MRI scan time. To accelerate the data acquisition process in MRI, less amount of data is acquired from the scanner which leads to artifacts in the reconstructed images. SENSitivity Encoding (SENSE) is a reconstruction algorithm in pMRI to remove aliasing artifacts from the undersampled multi coil data and recovers fully sampled images. The main limitation of SENSE is computing inverse of the encoding matrix. This work proposes the inversion of encoding matrix using Jacobi singular value decomposition (SVD) algorithm for image reconstruction on GPUs to accelerate the reconstruction process. The performance of Jacobi SVD is compared with Gauss–Jordan algorithm. The simulations are performed on two datasets (brain and cardiac) with acceleration factors 2, 4, 6 and 8. The results show that the graphics processing unit (GPU) provides a speed up to 21.6 times as compared to CPU reconstruction. Jacobi SVD algorithm performs better in terms of acceleration in reconstructions on GPUs as compared to Gauss–Jordan method. The proposed algorithm is suitable for any number of coils and acceleration factors for SENSE reconstruction on real time processing systems.     

基于差分曲率的各项异性扩散小波图像降噪算法研究

在$\gamma $放射性内污染修正均匀冗余阵列编码成像中,为了进一步减少使用最大似然估计(Maximum Likelihood Expectation Maximisation,MLEM)算法进行编码图像重建的伪影,并且提高重建的效率,本文提出了基于差分曲率的各项异性扩散小波图像降噪(Anisotropic Diffusion Wavelet Image Denoising based on Differential Curvature, 简称ADWIDDC)算法, 结合MLEM算法得到了改进的应用于编码成像的MLEM-ADWIDDC算法。该算法首先采用MLEM算法对探测器得到的投影数据进行图像重建,再利用互补成像方法消减近场伪影,最后采用ADWIDDC算法进一步降低图像伪影。模拟结果表明,对于131I源呈圆环分布的编码图像,以重建算法运行时间为195 s为截止条件,MLEM-ADWIDDC算法能够更好地去除伪影,重建的$\gamma $放射源图像纹理也更加清晰;对于131I源呈“CDUT”分布的编码图像,以重建图像信噪比达到5.10 dB为截止条件,本文的MLEM-ADWIDDC算法运行时间为98.36 s,比仅采用MLEM算法消耗的时间缩短了49%。     

ANTHEM: anatomically tailored hexagonal MRI

PURPOSE: This study aimed to investigate the use of anatomically tailored hexagonal sampling for scan-time and error reduction in MRI. MATERIALS AND METHODS: Anatomically tailored hexagonal MRI (ANTHEM), a method that combines hexagonal sampling with specific symmetry in anatomical geometry, is proposed. By using hexagonal sampling, aliasing artifacts are moved to regions where, due to the nature of the anatomy, aliasing is inconsequential. This can be used to either reduce scan time while maintaining spatial resolution or reduce residual errors in speedup techniques like UNFOLD and k-t BLAST/SENSE, which undersample k-space and unwrap fold-over artifacts during reconstruction. Computer simulations as well as phantom and volunteer studies were used to validate the theory. A simplified reconstruction algorithm for hexagonally sampled and subsampled k-space data was also used. RESULTS: A reduction in sampling density of 13.4% and 25% in each hexagonally sampled dimension was achieved for spherical and conical geometries without aliasing or reduction in spatial resolution. Optimal subsampling schemes that can be utilized by UNFOLD and k-t BLAST/SENSE were derived using hexagonal subsampling, which resulted in maximal, isotropic dispersal of the aliases. In combination with UNFOLD, ANTHEM was shown to move residual aliasing artifacts to the corners of the field of view, yielding reduced artifacts in CINE reconstructions. CONCLUSIONS: ANTHEM was successful in reducing acquisition time in conventional MRI and in reducing errors in UNFOLD imaging.     

Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm

Single-photon emission computerized tomography and positron emission tomography are essential medical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different acquisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose.     

基于自适应正则化的超分辨率重建方法

传统正则化超分辨重建得到的图像往往存在过度平滑或伪信息残留的问题,结合超分辨重建模型对重建图像伪信息的产生进行了分析,针对传统方法的不足提出了基于图像区域信息自适应的正则化方法,通过图像的区域信息将图像划分为平滑区与非平滑区域,对不同区域选用不同的先验模型进行约束。同时考虑人眼的视觉感知特性,结合区域信息实现正则化参数的自适应选取。实验结果表明该方法在抑制重建图像伪信息的同时能有效保护细节,效果要优于传统方法与单一的先验模型约束,对于红外与可见光图像重建效果的提升提供了一定的理论参考。     

Stationary wavelet transform for under-sampled MRI reconstruction

In addition to coil sensitivity data (parallel imaging), sparsity constraints are often used as an additional l_p-penalty for under-sampled MRI reconstruction (compressed sensing). Penalizing the traditional decimated wavelet transform (DWT) coefficients, however, results in visual pseudo-Gibbs artifacts, some of which are attributed to the lack of translation invariance of the wavelet basis. We show that these artifacts can be greatly reduced by penalizing the translation-invariant stationary wavelet transform (SWT) coefficients. This holds with various additional reconstruction constraints, including coil sensitivity profiles and total variation. Additionally, SWT reconstructions result in lower error values and faster convergence compared to DWT. These concepts are illustrated with extensive experiments on in vivo MRI data with particular emphasis on multiple-channel acquisitions.     

Autocalibrated parallel imaging reconstruction with sampling pattern optimization for GRASE: APIR4GRASE

PurposeTo reduce artifacts and scan time of GRASE imaging by selecting an optimal sampling pattern and jointly reconstructing gradient echo and spin echo images.MethodsWe jointly reconstruct images for the different echo types by considering these as additional virtual coil channels in the novel Autocalibrated Parallel Imaging Reconstruction with Sampling Pattern Optimization for GRASE (APIR4GRASE) method. Besides image reconstruction, we identify optimal sampling patterns for the acquisition. The selected optimal patterns were validated on phantom and in-vivo acquisitions. Comparison to the conventional GRASE without acceleration, and to the GRAPPA reconstruction with a single echo type was also performed.ResultsUsing identified optimal sampling patterns, APIR4GRASE eliminated modulation artifacts in both phantom and in-vivo experiments; mean square error (MSE) was reduced by 78% and 94%, respectively, compared to the conventional GRASE with similar scan time. Both artifacts and g-factor were reduced compared to the GRAPPA reconstruction with a single echo type.ConclusionAPIR4GRASE substantially improves the speed and quality of GRASE imaging over the state-of-the-art, and is able to reconstruct both spin echo and gradient echo images.