新的Cauchy-Schwarz距离函数与多模态医学图像配准

信息论测度,特别是Shannon互信息是多模态图像配准的一种重要方法,但除了互信息之外,仍然存在其它的函数来实现这一任务。对互信息、Kullback-Leibler距离和Shannon不等式之间相互关系作了分析,根据这些关系和不等式理论,提出了新的Cauchy-Schwarz距离,并将这一距离测度用于多模态医学图像的配准处理。从计算速度、噪声容忍性、测度函数图形的特点和图像窗口大小影响等几个方面,通过MR和PET医学图像的实验分析,对新的Cauchy-Schwarz距离测度和典型的Shannon信息论测度进行了分析比较。实验结果表明,新的Cauchy-Schwarz距离测度函数同样可以用于多模态图像配准,而且有着更强的噪声容忍性和更为节省的计算量。     

基于尺度不变特征变换和区域互信息优化的多源遥感图像配准

为了进一步提高遥感图像配准精度, 提出了尺度不变特征变换(SIFT)结合区域互信息优化的遥感图像配准方法. 首先利用混沌序列的随机性和遍历性, 提出一种混沌量子粒子群优化(CQPSO)算法, 在量子粒子群优化(QPSO)算法迭代陷入早熟收敛时, 采用一种新的机理引入混沌序列, 进化粒子克服早熟. 图像配准算法分为预配准和精配准两个过程. 基于SIFT算法提取特征点, 经匹配和有效地外点排除完成预配准, 然后对匹配特征点坐标进行亚像素级微调, 通过最小二乘法求得一系列匹配参数构造初始粒子群, 最后利用混沌量子粒子群优化区域互信息完成精配准, 得到最优匹配参数. 用一些标准测试函数对所提出的CQPSO和QPSO及粒子群优化(PSO)算法进行了实验比较, 另外, 对SIFT, SIFT结合PSO算法优化区域互信息, SIFT结合QPSO算法优化区域互信息和SIFT结合CQPSO算法优化区域互信息(SRC)等四种算法进行了不同分辨率遥感图像配准实验比较和不同时相遥感图像配准实验比较, 实验结果验证了所提出的CQPSO算法的优越性和SRC配准方法的有效性.     

基于均值距离测度的医学图像配准

针对互信息测度在配准医学图像时易陷入局部极值、速度慢的缺点,提出了基于均值不等式的均值距离测度.首先根据均值不等式推导出5种均值距离测度：方根-算术均值距离(SAM)、方根-几何均值距离(SGM)、方根-调和均值距离(SHM)、算术-几何均值距离(AGM)、算术-调和均值距离(AHM).然后通过人体脑部CT/MR和MR-T1/PD图像的刚体配准实验,从函数曲线、配准精度、计算时间和收敛性能方面,对互信息与5种均值距离信息测度进行了比较与分析.实验结果表明,在不损失配准精度的前提下,AHM和SAM测度可以获得更快的配准速度,对噪声有很强的鲁棒性.     

Co-registration method for photoacoustic imaging and laser speckle imaging

Combining photoacoustic (PA) imaging with laser speckle (LS) imaging (LSI) can simultaneously determine total hemoglobin concentration (HbT), hemoglobin oxygen saturation (SO2), and blood flow rates. Thus,the co-registration of PA and LS images is important in physiological studies and pathological diagnosis.This letter presents a co-registration algorithm combining mutual information with the maximum betweenclass variance segmentation method (Otsu method). The mutual information and Otsu method are used to provide the registration measure criterion and image feature recognition, respectively. The evaluation results show that the registration function possesses a single maximum peak and high smoothness across the global co-registration district, indicating a robust behavior. Moreover, this method has good registration accuracy, and the fusion result simultaneously visualizes the separate functional information of two kindsof images.     

Study of mutual information multimodality medical image registration based on modified simplex optimization method

Because of a different imaging mechanism and highly complexity of body tissues and structures. Different modality medical images provide non-overlay complementary information. This has very important significance for multimodal medical image registration. Image registration is the first and key part of problem to be solved in the integrations. When the spatial position of two medical images is same, the registration could be achieved. For two CT and PET images, the principal axis method is adopted to achieve the rough registration. The modified simplex algorithm is employed to implement global search using the mutual information as similarity measure. The initial registration parameters are achieved through principal axis Based on the results of test, improved simplex method can adjust reflecting distance. Stepped-up optimization algorithm on the new experimental points through the methods of “reflection”, “enlargement”, “shrinkage” or “global systolic”. A mutual information registration based on modified simplex optimization method is presented in this paper to improve the speed of medical image registration.Results indicate that the proposed registration method prevents the optimizing process from falling into local extremum and improves the convergence speed while keeping the precision. The accurate registration of multimodal image with different resolutions is achieved.     

Local information‐distance thermodynamics of molecular fragments

The Fisher information contained in a probability distribution is summarized. The corresponding measures of the information distance, relative to the reference probability density, are introduced and discussed. These concepts are designed as analogues of the Kullback‐Leibler directed divergence and Kullback's divergence. For these alternative measures of the missing information the equilibrium (“stockholder”) scheme of Hirshfeld, of a division of the molecular electron density into the subsystem components, is derived from the minimum principle of the local or global entropy deficiency relative to the free‐subsystem (“promolecule”) reference. The local information distance densities are used to describe instantaneous electron distributions in molecular subsystems within a thermodynamic‐like approach to the density fluctuations and irreversible processes. The key concepts of such a local irreversible “thermodynamics” are introduced. They include the corresponding local affinities (forces) and the conjugate fluxes (responses), which together determine the local entropy deficiency source. These quantities depend on the adopted measure of the information distance and selected state‐parameters. For each such representation the relevant Onsager‐type reciprocity relations can be derived, which reflect the symmetries between the linear effects of affinities on fluxes.     

Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects

Deformation-based morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by nonrigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared nonrigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established nonrigid registration algorithms using 13 subjects with Williams syndrome and 13 normal control subjects. The five nonrigid registration algorithms include the following: (1) the adaptive bases algorithm, (2) the image registration toolkit, (3) The FSL nonlinear image registration tool, (4) the automatic registration tool, and (5) the normalization algorithm available in Statistical Parametric Mapping (SPM8). Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. Some regions are detected by several algorithms, but their extent varies. Others are detected only by a subset of the algorithms. Based on these results, we recommend using more than one algorithm when performing DBM studies.     

基于成像光通信的时间-空间扩频混合光码分多址编码方案

为了在成像光通信中充分利用时间和空间两种频带资源,以成像光通信为基础,提出一种利用二维光正交Pattern码结合时域扩频实现光码分多址(OCDMA)编码的新方案。分析在该方案中存在的多址干扰噪声,并给出了噪声的概率密度函数,然后讨论由多址噪声引起的误码率与判决门限、用户数、码长积和码重积之间的关系。在相同的码容量下与时域扩频光码分多址编码和空间扩频光码分多址编码方案相比,该方案能降低对相关器件性能(时域码片数量和空间像素规模)的要求,而且还可获得更小的误码率。最后给出编码解码的光学实现方案。     

基于变分推断的磁共振图像群组配准

为解决基于深度学习的成对配准方法精度低和传统配准算法耗时长的问题,本文提出一种基于变分推断的无监督端到端的群组配准以及基于局部归一化互相关（NCC）和先验的配准框架,该框架能够将多个图像配准到公共空间并有效地控制变形场的正则化,且不需要真实的变形场和参考图像．该方法得到的预估变形场可建模为概率生成模型,使用变分推断的方法求解;然后借助空间转换网络和损失函数来实现无监督方式训练．对于公开数据集LPBA40的3D脑磁共振图像配准任务,测试结果表明：本文所提出的方法与基线方法相比,具有较好的Dice得分、运行时间少且产生更好的微分同胚域,同时对噪声具有鲁棒性．     

Robust visual correspondence computation using monogenic curvature phase based mutual information

Visual correspondence has been a major research topic in the fields of image registration, 3D reconstruction, and object tracking for some decades. However, due to the radiometric variations of images, conventional approaches fail to produce robust matching results. The traditional method of intensity-based mutual information performs very good for global variations between images, however, its performance degrades in the case of local radiometric variations. Monogenic curvature phase information, as an important local feature of the image, has the advantage of being robust against brightness variation. Hence, in this Letter, we propose an approach to compute the visual correspondence by coupling the advantages of mutual information and monogenic curvature phase. Experimental results demonstrate that the proposed approach can work robustly under radiometric variations.     

基于MISR数据反演渤海湾气溶胶光学厚度

利用Terra卫星的MISR传感器数据进行渤海湾上空气溶胶反演的初步研究。采用分区暗像元的方法进行反演,传统暗像元大气校正算法认为研究区域上空的气溶胶光学厚度呈均匀分布状态。针对传统暗像元算法的不合理性, 将渤海湾划分为7个子区域, 每个子区域利用传统暗像元算法估算其气溶胶光学厚度, 然后结合空间插值算法获取整个渤海湾的气溶胶光学厚度信息。研究结果表明: 渤海湾上空的气溶胶光学厚度呈沿海岸线高,近海区低的阶梯分布模式,与传统暗像元算法相比, 分区暗像元算法综合考虑了水体上空气溶胶光学厚度空间分布的不均匀性, 有利于改善大气校正的精度。     

Steady-state probability density function in wave turbulence under large volume limit

We investigate the possibility for two-mode probability density function(PDF) to have a non-zero flux steady state solution.We take the large volume limit so that the space of modes becomes continuous.It is shown that in this limit all the steady-state two-or higher-mode PDFs are the product of one-mode PDFs.The flux of this steady-state solution turns out to be zero for any finite mode PDF.     

Fusion method of infrared and visible images based on neighborhood characteristic and regionalization in NSCT domain

On fusing infrared and visible image, the traditional fusion method cannot get the better image quality. Based on neighborhood characteristic and regionalization in NSCT (Nonsubsampled Contourlet Transform) domain, the fusion algorithm was proposed. Firstly, NSCT was adopted to decompose infrared and visible images at different scales and directions for the low and high frequency coefficients, the low frequency coefficients which were fused with improving regional weighted fusion method based on neighborhood energy, and the high-frequency coefficients were fused with multi-judgment rule based on neighborhood characteristic regional process. Finally, the coefficients were reconstructed to obtain the fused image. The experimental results show that, compared with the other three related methods, the proposed method can get the biggest value of IE (information entropy), MI(VI,F) (mutual information from visible image), MI(VI,F) (mutual information from infrared image), MI (sum of mutual information), and Q^AB/F (edge retention). The proposed method can leave enough information in the original images and its details, and the fused images have better visual effects.     

基于图像集拓扑中心的群体配准方法

传统的图像配准通常指定一幅参考图像在配准过程中保持不变,将另一幅图像变换到参考图像空间,使得两幅图像在空间上互相匹配,从而可以精确比较两者之间的差异.针对多幅个体差异较大的图像配准问题,如果指定一幅作为参考,将其他图像配准到参考图像空间,则会引入该幅参考图像的个体形状偏差,从而影响最终的对比结果.为此,本文首先介绍了目前针对该问题的主要解决方法,然后提出了基于图像集拓扑中心的群体配准方法——TopologyCenter.为验证所提出的群体配准方法的性能,通过使用国外公开的数据集,详细比较了本文提出的方法与当前两种主要方法的群体配准结果的差异.实验结果表明,本文提出的方法具有更小的群体配准偏差,群体配准结果更好;同时,在对实验结果的评价中,本文还提出了一种简捷的群体偏差度量指标.     

Relay selection scheme based on deep reinforcement learning in wireless sensor networks

Cooperative communication technology has realized the enhancement in the wireless communication system’s spectrum utilization rate without resorting to any additional equipment; additionally, it ensures system reliability in transmission, increasingly becoming a research focus within the sphere of wireless sensor networks (WSNs). Since the selection of relay is crucial to cooperative communication technology, this paper proposes two different relay selection schemes subject to deep reinforcement learning (DRL), in response to the issues in WSNs with relay selection in cooperative communications, which can be summarized as the Deep-Q-Network Based Relay Selection Scheme (DQN-RSS), as well as the Proximal Policy Optimization Based Relay Selection Scheme (PPO-RSS); it further compared the commonly used Q-learning relay selection scheme (Q-RSS) with random relay selection scheme. First, the cooperative communication process in WSNs is modeled as a Markov decision process, and DRL algorithm is trained in accordance with the outage probability, as well as mutual information (MI). Under the condition of unknown instantaneous channel state information (CSI), the best relay is adaptively selected from multiple candidate relays. Thereafter, in view of the slow convergence speed of Q-RSS in high-dimensional state space, the DRL algorithm is used to accelerate the convergence. In particular, we employ DRL algorithm to deal with high-dimensional state space while speeding up learning. The experimental results reveal that under the same conditions, the random relay selection scheme always has the worst performance. And compared to Q-RSS, the two relay selection schemes designed in this paper greatly reduce the number of iterations and speed up the convergence speed, thereby reducing the computational complexity and overhead of the source node selecting the best relay strategy. In addition, the two relay selection schemes designed and raised in this paper are featured by lower-level outage probability with lower-level energy consumption and larger system capacity. In particular, PPO-RSS has higher reliability and practicability.     

Global Analysis of Response in the Piezomagnetoelastic Energy Harvester System under Harmonic and Poisson White Noise Excitations

The piezomagnetoelastic energy harvester system subjected to harmonic and Poisson white noise excitations is studied by using the generalized cell mapping method. The transient and stationary probability density functions(PDFs) of response based on the global viewpoint are obtained by the matrix analysis method. Monte Carlo simulation results verify the accuracy of this method. It can be observed that evolutionary direction of transient and stationary PDFs is in accordance with the unstable manifold for this system, and a stochastic P-bifurcation occurs as the intensity of Poisson white noise increases. This study presents an efficient numerical tool to solve the stochastic response of a three-dimensional dynamical system and provides a new idea to analyze the energy harvester system.     

Mutual Information and Quantum Discord in Quantum State Discrimination with a Fixed Rate of Inconclusive Outcomes

We studied the mutual information and quantum discord that Alice and Bob share when Bob implements a discrimination with a fixed rate of inconclusive outcomes (FRIO) onto two pure non-orthogonal quantum states, generated with arbitrary a priori probabilities. FRIO discrimination interpolates between minimum error (ME) and unambiguous state discrimination (UD). ME and UD are well known discrimination protocols with several applications in quantum information theory. FRIO discrimination provides a more general framework where the discrimination process together with its applications can be studied. In this setting, we compared the performance of optimum probability of discrimination, mutual information, and quantum discord. We found that the accessible information is obtained when Bob implements the ME strategy. The most (least) efficient discrimination scheme is ME (UD), from the point of view of correlations that are lost in the initial state and remain in the final state, after Bob’s measurement.     

Cascade-like and scaling behavior of wind velocity increments in the atmospheric surface layer

By using a large amount of data collected in the atmospheric surface layer, we analyze the probability density functions (PDFs), the probability of return and the moments of wind velocity increments. Results show that the PDFs change from the non-Gaussian long-tailed distributions to Gaussian with the increase of time scales. This is similar to what has been observed and interpreted as an indication of cascade in the fully developed homogeneous and isotropic turbulence. Besides, both the probability of return and the moments are found to be scaling with time scales. We then compare above results with the truncated Lévy flights and the log-normal PDF model. It is found that although both models show the cascade-like behavior in the PDFs and the scaling behavior in the probability of return and the moments under some conditions, they are not good enough for quantitatively describing the random process of wind velocity increments.     

压缩感知同步扫描重建及其采样方案的研究

压缩感知(compressed sensing,CS)-磁共振成像(magnetic resonance imaging,MRI)技术使用随机欠采样的k空间数据来重建图像,大大提高了成像速度.但典型的CS重建很费时,这也是CS-MRI临床应用的主要障碍之一.针对这一问题,该文提出了在扫描时同步进行CS图像重建的方案.在同步重建的过程中,可以实时显示重建图像的结果,用户可以根据图像质量来决定何时终止扫描,这样可以在节约扫描和重建时间的同时,更好地控制图像质量.由于预先无法确定最终的采样率,因此传统的变密度随机采样方法并不完全适用.该文设计了适用于同步重建过程的采样模式生成方案,同时提出了分段采样方法,把采样过程分为两个阶段,不同阶段使用不同的概率密度函数(probability density function,PDF)确定待采样的相位编码行.模拟实验的结果表明,与使用单一密度函数的采样方案相比,分段采样方案能够在整个同步扫描重建过程中始终获得更好的图像.     

Extraction of physical laws from joint experimental data

The extraction of a physical law y=y_o(x) from joint experimental data about x and y is treated. The joint, the marginal and the conditional probability density functions (PDF) are expressed by given data over an estimator whose kernel is the instrument scattering function. As an optimal estimator of y_o(x) the conditional average is proposed. The analysis of its properties is based upon a new definition of prediction quality. The joint experimental information and the redundancy of joint measurements are expressed by the relative entropy. With the number of experiments the redundancy on average increases, while the experimental information converges to a certain limit value. The difference between this limit value and the experimental information at a finite number of data represents the discrepancy between the experimentally determined and the true properties of the phenomenon. The sum of the discrepancy measure and the redundancy is utilized as a cost function. By its minimum a reasonable number of data for the extraction of the law y_o(x) is specified. The mutual information is defined by the marginal and the conditional PDFs of the variables. The ratio between mutual information and marginal information is used to indicate which variable is the independent one. The properties of the introduced statistics are demonstrated on deterministically and randomly related variables.