基于约束共轭梯度的高能闪光照相3维重建算法

 针对高能闪光照相系统成像信噪比低的特点，提出了3维约束共轭梯度算法，该算法基于3维重建理论来重建方程，利用约束共轭梯度法迭代求图像重建的最优解。数值模拟结果表明：采用3维约束共轭梯度算法能有效改善高能闪光照相重建图像轴线噪声大的问题，是一种具有很高抗噪能力的闪光照相图像重建算法。     

一种基于约束共轭梯度的闪光照相图像重建算法

 针对闪光照相系统成像信噪比低的特点,提出了正则化预优约束共轭梯度算法（RPCCG）。RPCCG算法在闪光照相重建方程中引入Tikhonov正则化准则,利用预优约束共轭梯度法迭代求图像重建的最优解。数值试验表明,采用最小二乘+平滑准则的RPCCG算法是一种具有较高的抗噪能力的有效闪光照相图像重建算法,具有良好的收敛性和稳定性以及较高的重建精度。     

种基于偏微分方程约束的闪光照相图像重建算法

 针对闪光照相图像信噪比低的特点,提出了一种基于偏微分方程基于非线性PDE的约束的图像重建算法,该算法在重建迭代过程中引入了基于非线性PDE的平滑约束来抑制图像噪声,同时保护图像边缘。数值试验结果表明:相比于Landweber和预优约束共轭梯度（PCCG）重建算法,新算法具有更强的抗噪能力和边缘保护能力,是一种更加有效的闪光照相图像重建算法。     

基于约束共轭梯度的高能闪光照相图像复原算法

 针对闪光照相系统模糊较大、成像信噪比低的特点,提出了一种基于约束共轭梯度的闪光照相图像复原算法,将闪光照相图像复原问题转化为一个约束优化问题,引入基于非负、中值滤波和偏微分方程的光滑约束条件,并利用约束共轭梯度法迭代求最优解。数值试验表明,该算法能较好再现图像边缘信息,复原出的图像在信噪比和视觉方面都有较大提高。     

基于极大似然模型和期望最大化算法的闪光图像重建

针对闪光照相图像低信噪比的特点,研究了带约束的基于极大似然模型和期望最大化算法（ML-EM）的闪光照相图像重建算法。该算法在ML-EM迭代重建算法的基础上,根据闪光照相图像低信噪比的特点及被重建客体具有分段平滑的先验信息,在迭代重建的过程中进行了相应的噪声抑制,抑制了噪声对重建结果的影响,同时很好地保持了客体的边界特征。数值模拟结果表明,基于噪声约束的ML-EM重建算法能取得较好的重建效果。     

基于约束优化的闪光照相图像重建算法

针对闪光照相图像受模糊及噪声影响的问题,提出了一种基于约束优化的闪光照相图像重建算法。该算法建立基于平行束投影的正向成像矩阵,并通过嵌入模糊矩阵表达成像过程中的模糊因素,采用最速下降法求解重建问题。在算法中设计了预优矩阵以提高迭代重建速度,利用客体密度值非负、密度分布分段光滑并含有阶跃性边界的先验知识,设计和采用了非负约束、光滑约束及广义变分边界约束条件。对仿真FTO客体图像及实际闪光照相图像的重建结果表明,基于约束优化的重建算法具有良好的边界保持能力及噪声抑制能力,可以有效提高图像重建质量。     

由少量投影数据快速重建图像的迭代算法

针对由少最角度的投影数据重建CT图像的问题,提出了一种改进的基于图像总变差最小的迭代重建算法.该算法采用共轭梯度法求图像总变差最小,并在迭代过程中采用了多分辨迭代技术.用模拟的投影数据和实际扫描数据进行了重建数值实验.实验结果表明该算法不但提高了重建图像质量,也同时显著提高了迭代图像的收敛速度.     

基于贝叶斯准则的闪光照相图像重建

 针对闪光照相图像低信噪比的特点,研究了一种带约束的贝叶斯图像重建算法,较好地抑制了噪声对重建结果的影响,同时对细节信号具有较高的保持能力。该算法以贝叶斯重建为基础,在重建过程中考虑了闪光照相图像的受模糊影响比较严重的特点,引入了重建结果具有平滑性的先验信息进行约束,以提高重建结果的信噪比。通过在迭代过程中对重建结果进行平滑性约束以提高重建质量。数值模拟结果表明,该方法在闪光照相图像重建中具有较好的抗噪能力和边界保持能力。     

共轭梯度算法在高能X光照相密度重建中的应用

高能X光照相的密度重建方法主要有傅立叶变换重建、滤波反投影重建、代数法重建等。本文将共轭梯度算法用于高能X光照相的密度重建。采用了标准的共轭梯度程序并作了修改，可以根据实际需求加入一定的约束条件。该程序在有限数据下也能很好地运行。这种方法将被重建客体的模拟与客体的辐射照相投影联系起来。首先，以已知数据为依据，产生客体的一个初始模型。然后，用射线追踪法模拟这一客体的辐射照相。共轭梯度算法将该辐射照相与实际测量的辐射照相投影做比较找出最大可能解。循环迭代，直到实际测量的和计算得到的辐射照相之间的差别足够小(小到令人满意)。     

基于全变分正则化的高能闪光照相消模糊图像重建算法

 针对高能闪光照相投影图像消模糊难度大的问题,提出了一种基于全变分正则化的消模糊图像重建算法,该算法根据闪光照相的成像特点,将客体的纵向截面作为一个整体来进行建模,并在重建方程中考虑了模糊因素,然后采用全变分范数作为正则项,构建了用于消模糊图像重建的展平泛函,将消模糊图像重建问题转化为能量泛函极小化问题,通过固定点迭代算法求解图像重建问题的最小化解。数值模拟结果表明：该算法由于考虑了闪光照相成像时的图像模糊因素,在重建时能够较好地消除模糊对重建结果的影响,在抑制噪声的同时能较好地保持图像的边缘信息,有利于提高重建图像的质量。     

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.     

Research on the chaos recognition method based on differential entropy

Phase space reconstruction is the first step to recognizing the chaos from observed time series. On the basis of differential entropy, this paper introduces an efficient method to estimate the embedding dimension and the time delay simultaneously. The differential entropy is used to characterize the disorder degree of the reconstructed attractor. The minimum value of the differential entropy corresponds to the optimum set of the reconstructed parameters. Simulated experiments show that the original phase space can be effectively reconstructed from time series, and the accuracy of the invariants in phase space reconstruction is greatly improved. It provides a new method for the identification of chaotic signals from time series.     

Imaging tumor angiogenesis by use of combined near-infrared diffusive light and ultrasound

A novel two-step reconstruction scheme using a combined near-infrared and ultrasound technique and its utility in imaging distributions of optical absorption and hemoglobin concentration of breast lesions are demonstrated. In the first-step image reconstruction, the entire tissue volume is segmented based on initial coregistered ultrasound measurements into lesion and background regions. Reconstruction is performed by use of a finer grid for lesion region and a coarse grid for the background tissue. As a result, the total number of voxels with unknown absorption can be maintained on the same order of total measurements, and the matrix with unknown total absorption distribution is appropriately scaled for inversion. In the second step, image reconstruction is refined by optimization of lesion parameters measured from ultrasound images. It is shown that detailed distributions of wavelength-dependent absorption and hemoglobin concentration of breast carcinoma can be obtained with the new reconstruction scheme.     

Real-time Adaptive Optics with a Twisted Nematic Liquid Crystal Light Modulator Controlled by the Wave Front Reconstruction Sensor

We propose adaptive optics constructed with a new principle. In this system, numerical phase reconstruction algorithm is incorporated with the Hartmann wave front sensor and the phase compensator is driven to the conjugate of the input phase distortion at each time step. The computer simulation shows a sufficient robustness and swiftness of the wave front reconstruction sensor. Then, the experimental system is configured putting special emphasis on the simplicity and feasibility of the system. A small 2-dimensional grid mask is used in the Hartmann sensor, and a twisted nematic phase modulator with a response time of 30 ms is used as the phase compensator. The control system has a simple open loop setup using a phase reconstruction algorithm. This experimental system was effective not only for static phase distortion, but also for the dynamic phase perturbation induced by a thermal convection.     

Three-dimensional profile measurement of small lens using subpixel localization with color grating

In this paper a measurement method of three-dimensional profiles and a reconstruction system using subpixel localization with color gratings projection is described. The system has the effects of identical contrast on gratings for easier identification, switchable picture-in-picture on the display, and adjustable gratings with an adjustment module.The measurement method includes the following: the projection step; image extraction step; image fine-tuning step; subpixel localization processing step; and reconstruction step. A projection apparatus emits a grating towards a small lens under measurement, and forms a grating image on the small lens under measurement. The contrast values of the plurality of grating stripes of the grating image are identical. The grating image and picture-in-picture of a display can be fine-tuned and reconstruct the three-dimensional profiles of the small lens. This method can help improve measurement competence in the reverse engineering industry.     

Formation of a missing row reconstruction on a Cu(100) surface: An atom scale density functional theory based study

The oxygen-induced reconstruction of Cu(100) surfaces has been studied in great detail. Experimentally, missing row reconstruction occurs with an O coverage of 0.5 monolayer (ML). Several DFT-based calculations of vacancy-surface Cu pairs were performed at O coverage between 0 and 0.5 ML. No structure was identified in these calculations as being energetically favoured over the ideal Cu(100) structure. When a Cu atom (0.125 ML) was added to the system, a new energetically favourable missing row and added Cu-O-Cu row structure was found. It has been suggested that this structure is an important intermediate step towards the missing row formation. The transition from the missing and added row structure to the (2√2 × √2)R45^o-O reconstruction has the energetic requirement of very good binding sites for the Cu atoms, which can be found on the step boundaries. These results are in excellent agreement with the step edge growth and the formation of strongly anisotropic islands observed by Lahtonen et al. (J. Chem. Phys. 129 (2008) 124703).     

Numerical simulations of instabilities in the implosion process of inertial confined fusion in 2D cylindrical coordinates

In this paper, we introduce a multi-material arbitrary Lagrangian and Eulerian method for the hydrodynamic radiative multi-group diffusion model in 2D cylindrical coordinates. The basic idea in the construction of the method is the following: In the Lagrangian step, a closure model of radiation-hydrodynamics is used to give the states of equations for materials in mixed cells. In the mesh rezoning step, we couple the rezoning principle with the Lagrangian interface tracking method and an Eulerian interface capturing scheme to compute interfaces sharply according to their deformation and to keep cells in good geometric quality. In the interface reconstruction step, a dual-material Moment-of-Fluid method is introduced to obtain the unique interface in mixed cells. In the remapping step, a conservative remapping algorithm of conserved quantities is presented. A number of numerical tests are carried out and the numerical results show that the new method can simulate instabilities in complex fluid field under large deformation,and are accurate and robust.     

Novel local free energy minimum on the Cu(001) surface

High-resolution LEED (low-energy electron diffraction) data of Cu(001) reveal an uniaxial in-plane lattice reconstruction by 1%. One-dimensional nanogrooves induced by ion bombardment involve the creation of steps that enable this reconstruction. This is the first verification of van der Merwe's prediction of step facilitated reconstruction. We confirm the predicted dependence on step orientation: <100> steps allow stress-relief and <110> steps do not, consistent with the known elastic anisotropy. Similar behavior is predicted for other nonreconstructed (001) surfaces of 3d and 4d metals.     

Motion predicted online dynamic MRI reconstruction from partially sampled k-space data

In this work we address the problem of reconstructing dynamic MRI sequences in an online fashion, i.e. reconstructing the current frame given that the previous frames have been already reconstructed. The reconstruction consists of a prediction and a correction step. The prediction step is based on an Auto-Regressive AR(1) model. Assuming that the prediction is good, the difference between the predicted frame and the actual frame (to be reconstructed) will be sparse. In the correction step, the difference between the predicted frame and the actual frame is estimated from partially sampled K-space data via a sparsity promoting least squares minimization problem. We have compared the proposed method with state-of-the-art methods in online dynamic MRI reconstruction. The experiments have been carried out on 2D and 3D Dynamic Contrast Enhanced (DCE) MRI datasets. Results show that our method yields the least reconstruction error.     

Compressed Sensing MRI Using Sparsity Averaging and FISTA

Magnetic resonance imaging (MRI) is widely adopted for clinical diagnosis due to its non-invasively detection. However, acquisition of full k-space data limits its imaging speed. Compressed sensing (CS) provides a new technique to significantly reduce the measurements with high-quality MR image reconstruction. The sparsity of the MR images is one of the crucial bases of CS-MRI. In this paper, we present to use sparsity averaging prior for CS-MRI reconstruction in the basis of that MR images have average sparsity over multiple wavelet frames. The problem is solved using a Fast Iterative Shrinkage Thresholding Algorithm (FISTA), each iteration of which includes a shrinkage step. The performance of the proposed method is evaluated for several types of MR images. The experiment results illustrate that our approach exhibits a better performance than those methods that using redundant frame or a single orthonormal basis to promote sparsity.