激光反射断层成像相位恢复方法

针对激光反射断层成像过程中存在目标的平动和抖动所产生的旋转中心偏移导致重建图像错位形成伪影的问题,提出基于相位恢复技术的改进误差下降算法.该方法通过光强反复迭代得到相位分布,获得重构目标丢失的相位信息,通过增加初始约束条件以及空间域和频域的限制有效改善算法的收敛性.运用改进的误差下降算法,有效改善了相位恢复方法容易陷入局部极小解的问题,获得了优化的重构图像.仿真实验表明,三组投影数据重建图像的平均相对均方误差由0.774下降为0.551,能够有效消除图像重建伪影.外场实验结果表明此方法使激光反射断层成像系统分辨率得到有效改善.     

基于功率谱压缩-平移的多通道联合变换相关识别方法研究

为了充分利用光学相关识别系统的空间-频谱带宽,提高光学相关识别技术的并行处理效率和识别准确度,提出了基于功率谱压缩-平移算法的多通道联合变换相关识别方法,该方法将峰值位置变化的标准差作为相关识别的判据.在输入空间光调制器的不同区域加载场景图像和N幅参考图像,然后在图像上分别叠加经迭代算法优化的相位模板,使得场景图像的傅里叶谱和每一幅参考图像的傅里叶谱在频谱面的不同空间区域相干叠加.调节相位优化算法的约束参量,使得每个通道的联合变换功率谱互不干扰,可实现N个通道的并行处理.分析了不同优化相位的傅里叶谱的局域峰值杂波均值和相关输出的峰值位置变化标准差之间的关系,并将其作为相位优选的依据.研究结果表明,在所提实验和数值模拟参数条件下,多通道联合变换相关识别系统可以在不增加经典相关识别系统复杂度的前提下,实现16通道的并行处理,这对光学相关器的实用化具有重要意义.     

双即插即用能谱计算机断层重建算法

为降低X射线辐射剂量和提高成像效率,开发准确和高效的多能谱成像方法,提出一种具有双即插即用（PnP）框架的图像重建方法。该方法引入两个PnP正则化能量函数,分别对多通道图像内蕴低秩性与通道内图像稀疏性进行度量。首先以多通道图像间的相似块构造高维张量,然后引入张量加权核范数对张量低秩性进行刻画,并结合图像梯度域L0（伪）范数对通道内图像稀疏性进行刻画,最后设计基于交替方向乘子法的高效求解算法。为验证算法的可行性,开展模拟多通道光子计数采样图像重建实验。实验结果表明：与现有代表性方法相比,所提方法的峰值信噪比提升0.067 dB～1.89 dB,时间消耗约为代表性方法的25%;所提方法具有抑制伪影干扰和改善图像质量的优势,并且计算效率得到显著提升。     

相干X射线衍射成像的数字模拟研究

相位重建是实现X 射线相干衍射成像的关键, 它利用远场采集的样品傅里叶相干衍射花样、结合过采样理论,再采用迭代算法复原样品的相位信息. 文中采用数字模拟的方法, 利用小尺寸二维非周期性图形作为物场, 研究了过采样比对重构结果的影响, 研究发现, 迭代次数为1000 次时最佳过采样比的范围是3—7 之间. 利用噪声模拟方法, 研究了噪声对相位重建的影响, 找到了完成相位重建的噪声限是信噪比不能低于10. 分析了重构结果中孪生像以及随机平移的产生原因, 并给出了相应的解决办法, 结果表明, 此方法可有效地提高重构图像的质量. 关键词： 相干X射线衍射成像 过采样 相位重建算法 显微成像     

基于最小区域的锥束ART算法快速图像重建

针对锥束ART算法重建速度慢的问题,考虑到工业CT重建目标尺寸差异较大的特点,提出了一种基于最小重建区域的快速三维图像重建方法。由不同视角下的锥束投影构建最小区域包络,对最小区域包络进行膨胀处理,以消除重建目标边界附近所出现的伪影,在此基础上,给出了射线穿过最小重建区域的体素索引及权因子的计算。该方法能够根据重建目标的尺寸自适应地确定最小重建区域,从而最大限度地减少了计算量。实验结果表明,该方法不仅大幅度提高了锥束ART算法的重建速度,而且有效地提高了重建质量。     

一种八谱段滤光片成像系统设计

针对多光谱滤光片阵列成像采样率低,原始(Raw)数据稀疏所导致的重建图像模糊,高频信息丢失等问题,提出了一种新八谱段滤光片阵列分布方案,利用基于邻域梯度延伸方法对光谱Raw图像进行重建.首先基于二叉树生成法,在重复排列的4×4阵列中设计了一种等空间概率比的八谱段滤光片分布方案;然后针对传感器直接获取的稀疏Raw图像,计算各谱段采样点的梯度信息,在保持图像结构特征和纹理信息的基础上,利用邻域采样点的像素值和梯度值对未采样点进行重建,从而获得完整的光谱图像信息;最后,基于已重建的八谱段光谱图像,采用伪逆矩阵法重构各像素位置的31波段光谱值.结果表明,相对于主流图像重建方法,本文算法提高了重建八谱段光谱图像的峰值信噪比、复合峰值信噪比,降低了光谱均方差,更好地保留了图像的纹理和边缘,有效降低了多光谱滤光片阵列成像中的颜色伪影和图像模糊等现象.     

时间维相位重建的改进算法

提出了一种时间维-相位重建的改进算法:利用折叠位相图进行时间相位展开以提高算法效率;推导并调整了基于时间相位展开算法初始条件从而减少所需的二维编码条纹图,增加了算法的实时性.从而可以更加有效地解决深度表面不连续和存在隔离物表面拓扑结构的景物相位重建问题.实验结果证明了本文所提出算法的可行性及有效性.     

基于时分复用的多平面彩色全息显示

深度分割复用（DDM）是一种常用的生成彩色纯相位全息图的方法,在重建单个彩色图像时能够取得良好的效果,但是在重建多平面彩色图像时,会不可避免地出现再现质量差和串扰的现象。提出一种基于时分复用生成多平面彩色纯相位全息图的迭代方法,该方法基于Gerchberg-Saxton(GS)算法,在记录全息图时,对每个通道平面施加幅度约束,重复此过程,彩色图像的红（R）、绿（G）和蓝色（B）通道信息被分别记录在三个纯相位全息图中。在再现时,RGB三色通道在相同的距离处重合,重建出目标彩色图像。展示了1幅、3幅和5幅彩色图像的重建结果,与DDM方法相比,所提方法明显提高了重建彩色图像的质量水平,有效避免了不同通道平面之间的串扰。数值模拟和光电再现均证明了所提方法的有效性。     

相干X射线衍射成像三维重建的数字模拟研究

利用相干X射线衍射成像“过采样”采集样品的远场相干衍射图样, 结合相位重建迭代算法重建物空间样品信息. 三维重建过程中, 边界约束条件是相位重建算法中最为关键的部分. 本文采用数字模拟的方法, 利用灰度值图像作为物空间的样品, 研究并实现了边界条件的自动寻找, 重建结果显示比以往采用较“松”的边界约束更为精确. 利用噪声模拟方法, 研究了衍射图样中不同噪声类型的滤除对重建结果的影响. 研究发现传统的去噪方法在高噪声情况下不能直接应用于相干X射线衍射成像, 并找到了适用于相干X射线衍射成像噪声滤除的有效方法. 研究表明, 此方法能非常有效地降低噪声对重建结果的影响. 利用模拟三维纳米金颗粒作为样品, 完成了对纳米金颗粒中电子密度分布的三维重建, 在有随机噪声的影响下, 也得到了很好的重建结果, 并找到了成功实现三维重建的噪声限为信噪比不低于27. 关键词： X射线相干衍射成像 过采样 三维相位重建 显微成像     

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%。     

Motion correction based reconstruction method for compressively sampled cardiac MR imaging

Respiratory motion during Magnetic Resonance (MR) acquisition causes strong blurring artifacts in the reconstructed images. These artifacts become more pronounced when used with the fast imaging reconstruction techniques like compressed sensing (CS). Recently, an MR reconstruction technique has been done with the help of compressed sensing (CS), to provide good quality sparse images from the highly under-sampled k-space data. In order to maximize the benefits of CS, it is obvious to use CS with the motion corrected samples. In this paper, we propose a novel CS based motion corrected image reconstruction technique. First, k-space data have been assigned to different respiratory state with the help of frequency domain phase correlation method. Then, multiple sparsity constraints has been used to provide good quality reconstructed cardiac cine images with the highly under-sampled k-space data. The proposed method exploits the multiple sparsity constraints, in combination with demon based registration technique and a novel reconstruction technique to provide the final motion free images. The proposed method is very simple to implement in clinical settings as compared to existing motion corrected methods. The performance of the proposed method is examined using simulated data and clinical data. Results show that this method performs better than the reconstruction of CS based method of cardiac cine images. Different acceleration rates have been used to show the performance of the proposed method.     

非相干照明条件下的ptychographic iterative engine成像技术

在传统多波长相干衍射成像理论的基础上提出适用于 X-射线和电子束等非相干光源照明成像的改进多波长ptychographic iterative engine 方法, 同时将小孔形状和照明光谱信息用于叠代计算, 可以在非相干照明条件下精确重建出物体的强度透射像和相位透射像, 并对光源带宽对重建精度的影响进行了分析, 对于解决如何在非相干照明条件下对大尺寸物体进行精确相位成像的问题具有较好的科研和实用价值.     

颅脑梯度回波成像:呼吸伪影和导航回波矫正

梯度回波序列是磁共振成像中常用的脉冲序列,然而梯度回波对主磁场波动非常敏感,呼吸等生理运动引起的信号波动会导致图像伪影.该文报道了采用导航回波技术获取呼吸运动导致的局部磁场波动,用以矫正图像回波中随时间变化的相位波动,并将该技术应用于三维多回波梯度回波成像和T2*定量图研究.研究结果显示:矫正前,相位波动幅度随回波时间增长而增大,模图和T2*定量图在相位编码方向有明显伪影,并且男女呼吸伪影水平有显著性差异;矫正后,相位波动幅度大幅下降,图像伪影水平有显著性下降.     

基于有限脉冲响应滤波器的数字全息零级像消除

针对数字全息中零级像的存在影响数字再现像的质量,分析数字全息图的记录、再现原理及频谱特性,提出了一种利用有限脉冲响应滤波器消除全息图数字再现中零级像的方法.该方法只需记录一幅数字全息图,不需要相移器材或其他辅助设备,直接利用数字图像处理对数字全息图在空域进行预处理,消除全息再现时的零级像干扰.对比了数字模拟和实验拍摄到的全息图在应用有限脉冲响应滤波器消除零级像前后的再现结果,表明该方法可消除零级衍射像,改善重建像质量,并且算法简单.     

Phase deviation analysis and phase retrieval for partial intensity saturation in phase-shifting projected fringe profilometry

Intensity saturation may take place as a sinusoidal fringe pattern is projected onto an object which has a relative high reflective index on some regions of the surface. If a phase-shifting method is used, the illuming light intensities at the same point of the object may have different values for each projected phase-shifting fringe pattern. Therefore, when the intensity at a point of the object exceeds the saturation level for a certain phase step of projected fringe pattern, other intensities obtained at the same point with different phase steps of projected fringe patterns do not exceed the saturation level. This kind of saturation is defined as partial intensity saturation. In the case of partial intensity saturation, a relative larger phase error is introduced when a conventional phase reconstruction algorithm is used in the phase-shifting projected fringe profilometry (PSPFP). To get rid of such disadvantage, an improved algorithm for phase reconstruction is proposed in this paper. By using the new algorithm, the effect of partial intensity saturation for the phase reconstruction can be decreased greatly and a good quality of reconstructed phase map can be obtained. Phase deviation of the reconstructed phase is also analyzed. Finally, an experimental result with PSPFP is presented to validate the feasibility of the proposed algorithm.     

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.     

Respiratory motion compensation using data binning in dynamic contrast enhanced golden-angle radial MRI

GRASP (Golden-Angle Radial Sparse Parallel MRI) is a data acquisition and reconstruction technique that combines parallel imaging and golden-angle radial sampling. The continuously acquired free breathing Dynamic Contrast Enhanced (DCE) golden-angle radial MRI data of liver and abdomen has artifacts due to respiratory motion, resulting in low vessel-tissue contrast that makes GRASP reconstructed images less suitable for diagnosis. In this paper, DCE golden-angle radial MRI data of abdomen and liver perfusion is sorted into different motion states using the self-gating property of radial acquisition and then reconstructed using GRASP. Three methods of amplitude-based data binning namely uniform binning, adaptive binning and optimal binning are applied on the DCE golden-angle radial data to extract different motion states and a comparison is performed with the conventional GRASP reconstruction. Also, a comparison among the amplitude-based data binning techniques is performed and benefits of each of these binning techniques are discussed from a clinical perspective. The image quality assessment in terms of hepatic vessel clarity, liver edge sharpness, contrast enhancement clarity and streaking artifacts is performed by a certified radiologist. The results show that DCE golden-angle radial trajectories benefit from all the three types of amplitude-based data binning methods providing improved reconstruction results. The choice of binning technique depends upon the clinical application e.g. uniform and adaptive binning are helpful for a detailed analysis of lesion characteristic and contrast enhancement in different motion states while optimal binning can be used when clinical analysis requires a single image per contrast enhancement phase with no motion blurring artifacts.     

PIE成像中周期性重建误差的研究

本文分析了PIE技术中周期性误差出现的根本原因,并在此基础上提出一种能明显减小此种误差的方法.通过将现有PIE成像技术中的定步长二维周期扫描变为步长和方向都不确定的随机二维扫描,可以根本上去除样品重建像中的周期性误差,从而得到准确的相位和振幅像,对提高PIE成像的精度有较好的现实意义.     

基于稀疏重建的磁共振图像尖峰噪声消除方法

磁共振图像K空间中的尖峰噪声会严重影响图像质量.该文在磁共振图像压缩感知的共轭梯度重建法的基础上,提出一种新的利用磁共振图像稀疏性进行尖峰噪声修复的方法.传统的共轭梯度重建是通过小波域迭代进行的,对于K空间的尖峰噪声的消除不是最适合.首先提出压缩感知的K空间重建算法,该算法与小波域重建等效.在此基础上,提出可以较好地修复尖峰噪声的K空间部分重建算法.即在迭代过程中,以图像的稀疏性作为约束条件,仅修改尖峰噪声所遮盖区域的数据,其他位置的数据保持不变.该算法与传统的插值算法及共轭梯度算法相比,能够更好地修复K空间尖峰噪声点,减少图像伪影,同时降低了对尖峰噪声定位准确性的要求.     

Importance of the (nabla) D term in frequency-resolved optical diffusion imaging

The effects of the approximation DD=0 that is often used in frequency-resolved optical diffusion imaging are examined. It is shown that this approximation can affect the performance of integral-equation-based approaches to optical diffusion imaging, such as the Born iterative method and the distorted Born iterative method. The approximation introduces errors into the calculation of data used in simulations, which can lead to misleading evaluations of reconstruction algorithms. Numerical calculations show the magnitude of these effects and the appearance of artifacts in reconstructed images when conventional inversion algorithms are applied to more accurately calculated data.