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。     

Beam hardening correction for a cone-beam CT system and its effect on spatial resolution

In this paper, we present a beam hardening correction (BHC) method in three-dimension space for a cone-beam computed tomography (CBCT) system in a mono-material case and investigate its effect on the spatial resolution. Due to the polychromatic character of the X-ray spectrum used, cupping and streak artifacts called beam hardening artifacts arise in the reconstructed CT images, causing reduced image quality. In addition, enhanced edges are introduced in the reconstructed CT images because of the beam hardening effect. The spatial resolution of the CBCT system is calculated from the edge response function (ERF) on different planes in space. Thus, in the CT images with beam hardening artifacts, enhanced ERFs will be extracted to calculate the modulation transfer function (MTF), obtaining a better spatial resolution that deviates from the real value. Reasonable spatial resolution can be obtained after reducing the artifacts. The 10% MTF value and the full width at half maximum (FWHM) of the point spread function with and without BHC are presented.     

Self-calibration using two same circles

Camera calibration is a fundamental step in 3D reconstruction and computer vision. Considering the easy accessibility of two same circles, a method for self-calibration based on two same circles is proposed. The proposed method does not need any prior knowledge and known camera parameters. By taking three photos of the object containing two same circles from different views, the close solution for intrinsic and extrinsic parameters are first obtained by the invariance of circular points and common tangent of two circles. Then the solution is refined by the nonlinear optimization. This method could get the intrinsic parameters as well as the extrinsic parameters without complicated matching process. Extensive results show the accuracy, robustness and wide applications of the proposed method.     

Real-time camera pose estimation based on volleyball court view

The use of technology in sports has increased in recent years. One of the most influential of these technologies is referee support systems. Team sports such as volleyball require accurate and robust tracking systems that do not affect either the players or the court. This paper introduces the application of intrinsic and extrinsic camera calibration in a 12-camera volleyball referee system. Intrinsic parameters are calculated by using the classic pinhole model and Zhang’s method. To perform extrinsic calibration in real time, the volleyball court is treated as a global calibration artifact. Calibration keypoints are defined as court-line intersections. In addition, a new keypoint detection algorithm is proposed. It enables achievement of an accurate camera pose in regard to the court. With all 12 cameras calibrated in a common coordinate system, a dynamic camera stereo pair creation is possible. Therefore, with known ball 2D image coordinates, the 3D real ball coordinates can be reconstructed and the ball trajectory can be estimated. The performance of the proposed method is tested on a synthetic data set, including 3Ds Max rendering and real data scenarios. The mean camera pose error calculated for data biased with keypoint detection errors is approximately equal to 0.013% of the measurement volume. For the real data experiment with a human hand phantom, it is possible to determine the presence of the human phantom on the basis of the ball reflection attitude.     

Cone-beam local reconstruction based on a Radon inversion transformation

The local reconstruction from truncated projection data is one area of interest in image reconstruction for computed tomography(CT),which creates the possibility for dose reduction.In this paper,a filtered-backprojection(FBP) algorithm based on the Radon inversion transform is presented to deal with the three-dimensional(3D) local reconstruction in the circular geometry.The algorithm achieves the data filtering in two steps.The first step is the derivative of projections,which acts locally on the data and can thus be carried out accurately even in the presence of data truncation.The second step is the nonlocal Hilbert filtering.The numerical simulations and the real data reconstructions have been conducted to validate the new reconstruction algorithm.Compared with the approximate truncation resistant algorithm for computed tomography(ATRACT),not only it has a comparable ability to restrain truncation artifacts,but also its reconstruction efficiency is improved.It is about twice as fast as that of the ATRACT.Therefore,this work provides a simple and efficient approach for the approximate reconstruction from truncated projections in the circular cone-beam CT.     

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。     

K-space trajectory mapping and its application for ultrashort Echo time imaging

MR images are affected by system delays and gradient field imperfections which induce discrepancies between prescribed and actual k-space trajectories. This could be even more critical for non-Cartesian data acquisitions where even a small deviation from the assumed k-space trajectory results in severe image degradation and artifacts. Knowledge of the actual k-space trajectories is therefore crucial and can be incorporated in the reconstruction of high quality non-Cartesian images. A novel MR method for the calibration of actual gradient waveforms was developed using a combination of phase encoding increments and subsequent detection of the exact time point at which the corresponding trajectory is crossing the k-space origin. The measured sets of points were fitted to a parametrical model to calculate the complete actual acquisition trajectory. Measurements performed on phantoms and volunteers, positioned both in- and off-isocenter of the magnet, clearly demonstrate the improvement in reconstructed ultrashort echo time (UTE) images, when information from calibration of k-space sampling trajectories is employed in the MR image reconstruction procedure. The unique feature of the proposed method is its robustness and simple experimental setup, making it suitable for quick acquisition trajectory calibration procedures e.g. for non-Cartesian radial fast imaging.     

Cardiac magnetic resonance imaging using radial k-space sampling and self-calibrated partial parallel reconstruction

Radial sampling has been demonstrated to be potentially useful in cardiac magnetic resonance imaging because it is less susceptible to motion than Cartesian sampling. Nevertheless, its capability of imaging acceleration remains limited by undersampling-induced streaking artifacts. In this study, a self-calibrated reconstruction method was developed to suppress streaking artifacts for highly accelerated parallel radial acquisitions in cardiac magnetic resonance imaging. Two- (2D) and three-dimensional (3D) radial k-space data were collected from a phantom and healthy volunteers. Images reconstructed using the proposed method and the conventional regridding method were compared based on statistical analysis on a four-point scale imaging scoring. It was demonstrated that the proposed method can effectively remove undersampling streaking artifacts and significantly improve image quality (P<.05). With the use of the proposed method, image score (1–4, 1=poor, 2=good, 3=very good, 4=excellent) was improved from 2.14 to 3.34 with the use of an undersampling factor of 4 and from 1.09 to 2.5 with the use of an undersampling factor of 8. Our study demonstrates that the proposed reconstruction method is effective for highly accelerated cardiac imaging applications using parallel radial acquisitions without calibration data.     

基于同心圆合成图像匹配的双目视觉标定

分析了双目视觉传感器的数学模型,提出了一种基于同心圆合成图像匹配的双目视觉传感器的标定方法。在测量范围内任意多次摆放同心圆靶标,由两台摄像机拍摄靶标图像。根据摄像机模型与已知同心圆在靶标坐标系上的位置关系,构造合成图像,将合成图像与观测图像进行相似度匹配,通过优化定位得到靶标上每个圆的圆心点图像坐标。利用左右图像对应的圆心图像坐标和双目视觉的约束关系,对双目视觉传感器参数进行非线性优化,并得到最优解。所提出的标定方法是在张正友方法的理论基础上,利用了图像的整体性进行的优化。实验结果表明,该方法提高了标定精度。     

Automatic calibration method of voxel size for cone-beam 3D-CT scanning system

For a cone-beam three-dimensional computed tomography (3D-CT) scanning system, voxel size is an important indicator to guarantee the accuracy of data analysis and feature measurement based on 3D-CT images. Meanwhile, the voxel size changes with the movement of the rotary stage along X-ray direction. In order to realize the automatic calibration of the voxel size, a new and easily-implemented method is proposed. According to this method, several projections of a spherical phantom are captured at different imaging positions and the corresponding voxel size values are calculated by non-linear least-square fitting. Through these interpolation values, a linear equation is obtained that reflects the relationship between the voxel size and the rotary stage translation distance from its nominal zero position. Finally, the linear equation is imported into the calibration module of the 3D-CT scanning system. When the rotary stage is moving along X-ray direction, the accurate value of the voxel size is dynamically exported. The experimental results prove that this method meets the requirements of the actual CT scanning system, and has virtues of easy implementation and high accuracy.     

Building an accurate 3D model of a circular feature for robot vision

In this paper, an accurate 3D model analysis of a circular feature is built with error compensation for robot vision. We propose an efficient method of fitting ellipses to data points by minimizing the algebraic distance subject to the constraint that a conic should be an ellipse and solving the ellipse parameters through a direct ellipse fitting method by analysing the 3D geometrical representation in a perspective projection scheme, the 3D position of a circular feature with known radius can be obtained. A set of identical circles, machined on a calibration board whose centres were known, was calibrated with a camera and did the model analysis that our method developed. Experimental results show that our method is more accurate than other methods.     

Research on camera calibration using new optimization strategy

An important task for stereo vision is camera calibration, whose goal is to obtain the intrinsic and extrinsic parameters of each camera. This paper proposes a new accurate calibration method with multilevel process of camera parameters. In order to improve the calibration accuracy, a sub-pixel corner detection method is presented. We start with several views of a planar calibration to obtain some intrinsic camera parameters and to build an accurate model with lens distortion on a planar calibration target. Flexibly making use of geometry imaging theory, our algorithm obtains all the parameters through logical organization of solving order, accordingly avoids obtaining possible local optimized problem when solving the non-linear equation, gets over the relativity influence of every unknown parameters of traditional calibration way, and makes the error distributed among the constraint relation of parameters. Experiments with real images are carried out to verify the image correction effect and numerical robustness of our results. Compared with classical calibration techniques, that use expensive equipment and complicated mathematical computation, the proposed technique, which was verified by experiment, achieves high accuracy and reliable parameters.     

一种基于FDK的锥束CT重建的改进方法

在实际的锥束CT扫描过程中,由于探测器的离散化,对每个探测器单元来说都有一定大小.那么相对于被扫描物体的每个体素点,在某一个角度下过它的射线打在探测器上是有一定面积的,如果取体素截面大小和探测器单元大小相近,过它的射线是分布在相邻的几个探测器单元上的,在重建过程中,如果依据落在各个探测器单元上的射线所占面积的大小考虑到那些探测器单元的信息对被重建体素点的影响,会提高重建图像的边缘清晰度,本论文利用实际的锥束扫描数据,采用传统的FDK方法和改进的FDK方法对物体重建,通过比较得出用新方法重建的图像边缘比传统FDK方法清晰,而且新方法还有抑制噪声的作用。     

锥束CT成像质量影响因素研究

CT成像质量受诸多因素影响,有必要系统地研究各因素带来的影响以得到更好的成像效果。基于兰州大学核科学与技术学院研制的锥束CT系统,在近探测器几何条件下,采用一铝制标准件,通过对比实验研究了投影采集范围及步长、管电压及管电流、焦点尺寸、样品在转台位置、硬化校正和图像优化等因素对CT系统成像质量的影响。结果表明,当投影采集完备时,投影采集范围对成像质量影响较小,减小扫描步长能提高成像质量;适当提高管电压能降低硬化伪影,提高管电流能减小图像噪声;较小的焦点尺寸能提高图像空间分辨率,但在近探测器几何条件下不明显;样品在转台位置不影响CT系统还原样品结构;硬化校正能明显消除硬化伪影;最后,对于单一材质样品通过阈值去噪能优化图像质量。以上研究为CT系统的研制和应用提供了参考。     

一种基于Radon逆变换的半覆盖螺旋锥束CT重建算法

半覆盖螺旋锥束计算机断层成像能够扩展传统螺旋锥束计算机断层成像的成像视野, 实现小面板探测器成像超视野物体. 但是, 各角度下的投影都存在数据截断, 会使重建结果中产生截断伪影, 降低图像质量. 本文提出了一种基于Radon逆变换的半覆盖螺旋锥束重建算法, 该算法在滤波时先使用局部算子, 再使用全局算子. 局部算子不受数据截断的影响, 并且降低了运算后的值由于数据截断所造成的不连续性, 因此, 减少了随后全局运算产生的截断误差. 仿真和实际实验结果均验证了本文算法的有效性. 和现有算法的对比也表明, 本文算法针对半覆盖螺旋锥束投影具有更强的截断伪影抑制能力, 能够有效提高重建图像的质量.     

A statistical iteration approach with energy minimization to sinogram noise reduction for low-dose X-ray CT

Low-dose CT imaging has been particularly used in modern medical practice for its advantage on reducing the radiation dose to patients. However, excessive quantum noise is present in low dose X-ray imaging along with the decrease of the radiation dose; thus, there are obvious streak-like artifacts in reconstructed images. The statistical iterative reconstruction approach applied to the noisy sinogram before a filtered back-projection (FBP) is a resolution to deal with the noisy problem. In this paper, the statistical property of the noise sinogram was considered to achieve a satisfactory image reconstruction and a statistical iterative method with energy minimization was proposed to address the problem of streak-like artifacts. Simulations were performed and indicated that the proposed method could suppress noise and obviously decrease streak-like artifacts in reconstructed images.     

工业CT图像边缘伪影校正

为了去除工业CT图像中的边缘伪影,提高CT图像的识别能力和尺寸测量精度,提出一种降低串扰的系数修正法。首先分析得出边缘伪影主要是由散射射线在相邻探测通道之间的串扰所导致,并给出了探测通道串扰的数学模型;然后根据数学模型设计实验方案,通过对影响串扰率的主要因素进行实验分析,得到串扰率随入射X射线能量和被测物体厚度变化关系,再通过最小二乘拟合得出投影数据关于串扰率的函数;最后利用此函数对投影数据进行校正,降低了串扰的影响。实验结果表明,探测器间一级串扰率约为9.0%,二级串扰率约为1.2%,其中一级串扰是造成边缘伪影的主要因素,采用本文方法能够有效地抑制边缘伪影,同时较好地保留了图像细节和边缘。     

A generalized method of converting CT image to PET linear attenuation coefficient distribution in PET/CT imaging

The accuracy of attenuation correction in positron emission tomography scanners depends mainly on deriving the reliable 511-keV linear attenuation coefficient distribution in the scanned objects. In the PET/CT system, the linear attenu- ation distribution is usually obtained from the intensities of the CT image. However, the intensities of the CT image relate to the attenuation of photons in an energy range of 40 keV-140 keV. Before implementing PET attenuation correction, the intensities of CT images must be transformed into the PET 511-keV linear attenuation coefficients. However, the CT scan parameters can affect the effective energy of CT X-ray photons and thus affect the intensities of the CT image. Therefore, for PET/CT attenuation correction, it is crucial to determine the conversion curve with a given set of CT scan parameters and convert the CT image into a PET linear attenuation coefficient distribution. A generalized method is proposed for con- verting a CT image into a PET linear attenuation coefficient distribution. Instead of some parameter-dependent phantom calibration experiments, the conversion curve is calculated directly by employing the consistency conditions to yield the most consistent attenuation map with the measured PET data. The method is evaluated with phantom experiments and small animal experiments. In phantom studies, the estimated conversion curve fits the true attenuation coefficients accurately, and accurate PET attenuation maps are obtained by the estimated conversion curves and provide nearly the same correction results as the true attenuation map. In small animal studies, a more complicated attenuation distribution of the mouse is obtained successfully to remove the attenuation artifact and improve the PET image contrast efficiently.     

单摄像机单投影仪结构光三维测量系统标定方法

系统参数的标定是结构光三维测量系统工作的基础,且参数标定的精度直接影响测量的精度,其中投影仪目前还存在标定过程复杂、精度较低等问题。为解决该问题,通过投影一组圆阵图案到一块本身带有特征圆的平板上,并由摄像机拍摄;基于二维射影变换理论,通过误差补偿法建立投影仪图像坐标和摄像机图像坐标的对应关系,利用该对应关系计算获取标定点的投影仪图像坐标;以标定点的两组图像坐标和世界坐标为初始值,使用非线性算法对系统进行全参数整体优化,完成系统的标定。实验验证了系统标定误差最大值小于0.05 mm,误差均方根小于0.03 mm,结果表明该方法标定过程简单,能够有效地提高标定精度,具有较广的适用性。     

Noise reduction for low-dose X-ray CT based on fuzzy logical in stationary wavelet domain

Apparent streak-like artifacts will present in reconstructed images due to excessive quantum noise in low-dose X-ray imaging process. Dealing with the noisy sinogram before a filtered back-projection (FBP) is a useful solution to solve this noise problem. In this paper, we proposed a novel noise restoration method combining wavelet and fuzzy logical technology for low-dose computed tomography (CT) sinogram. The method first utilizes stationary wavelet transform on the noisy sinogram, namely decomposes the sinogram to different resolution levels. And then, at each decomposed resolution level, a fuzzy shrinkage filter is applied to restore the noise-contaminated wavelet coefficients. Simulations were performed and indicated that the proposed method could significantly suppress noise and reduced streak-like artifacts in reconstructed images while at the same time maintaining the image sharpness.