High resolution dynamic cardiac MRI using partial separability of spatiotemporal signals with a novel sampling scheme

The partial separability (PS) of spatiotemporal signals has been exploited to accelerate dynamic cardiac MRI by sampling two datasets (training and imaging datasets) without breath-holding or ECG triggering. According to the theory of partially separable functions, the wider the range of spatial frequency components covered by the training dataset, the more accurate the temporal constraint imposed by the PS model. Therefore, it is necessary to develop a new sampling scheme for the PS model in order to cover a wider range of spatial frequency components. In this paper, we propose the use of radial sampling trajectories for collecting the training dataset and Cartesian sampling trajectories for collecting the imaging dataset. In vivo high resolution cardiac MRI experiments demonstrate that the proposed data sampling scheme can significantly improve the image quality. The image quality using the PS model with the proposed sampling scheme is comparable to that of a commercial method using retrospective cardiac gating and breath-holding. The success of this study demonstrates great potential for high-quality, high resolution dynamic cardiac MRI without ECG gating or breath-holding through use of the PS model and the novel data sampling scheme.     

An optimal robust digital image watermarking based on SVD using differential evolution algorithm

The main objective in developing a robust image watermarking technique is to obtain the highest possible robustness without losing the transparency. To achieve this objective, this paper presents a new optimal robust image watermarking technique based on singular value decomposition (SVD) using differential evolution algorithm (DE). The singular values (SV) of the host image are modified by multiple scaling factors to embed a watermark image. The modifications are optimised using DE to achieve maximum robustness and transparency Experimental results show that the proposed approach can effectively improve the quality of the watermarked image and the robustness of the embedded watermark against various attacks.     

Multi-focus image fusion based on robust principal component analysis and pulse-coupled neural network

Multi-focus image fusion combines multiple source images with different focus points into one image, so that the resulting image appears all in-focus. In order to improve the accuracy of focused region detection and fusion quality, a novel multi-focus image fusion scheme based on robust principal component analysis (RPCA) and pulse-coupled neural network (PCNN) is proposed. In this method, registered source images are decomposed into principal component matrices and sparse matrices with RPCA decomposition. The local sparse features computed from the sparse matrix construct a composite feature space to represent the important information from the source images, which become inputs to PCNN to motivate the PCNN neurons. The focused regions of the source images are detected by the firing maps of PCNN and are integrated to construct the final, fused image. Experimental results demonstrate that the superiority of the proposed scheme over existing methods and highlight the expediency and suitability of the proposed method.     

基于奇异值分解的光子相关光谱滤波方法研究

针对光子相关光谱颗粒测量法在测量超细纳米颗粒时,容易受噪声影响,导致拟合误差较大的问题,提出了一种基于奇异值分解的光子相关光谱滤波方法。其处理步骤为:利用颗粒系的光强自相关函数数据构造Hankel矩阵H;对矩阵进行奇异值分解;根据奇异值的大小分布,确定噪声级别和重建参数r;从重建矩阵H1中提取经滤波后的光强自相数据,再通过传统方法进行拟合,得到颗粒的粒径分布。实验中采用30nm标准乳胶球单分散颗粒系,以及30nm和100nm标准乳胶球双分散颗粒系进行实验对比。结果证明:基于奇异值分解的光子相关光谱滤波法有效地提高了测量准确性。     

A linear algorithm of the reference region model for DCE-MRI is robust and relaxes requirements for temporal resolution

Dynamic contrast enhanced MRI (DCE-MRI) has utility for improving clinical diagnoses of solid tumors, and for evaluating the early responses of anti-angiogenic chemotherapies. The Reference Region Model (RRM) can improve the clinical implementation of DCE-MRI by substituting the contrast enhancement of muscle for the Arterial Input Function that is used in traditional DCE-MRI methodologies. The RRM is typically fitted to experimental results with a non-linear least squares algorithm. This report demonstrates that this algorithm produces inaccurate and imprecise results when DCE-MRI results have low SNR or slow temporal resolution. To overcome this limitation, a linear least-squares algorithm has been derived for the Reference Region Model. This new algorithm improves accuracy and precision of fitting the Reference Region Model to DCE-MRI results, especially for voxel-wise analyses. This linear algorithm is insensitive to injection speeds, and has 300- to 8000-fold faster calculation speed relative to the non-linear algorithm. The linear algorithm produces more accurate results for over a wider range of permeabilities and blood volumes of tumor vasculature. This new algorithm, termed the Linear Reference Region Model, has strong potential to improve clinical DCE-MRI evaluations.     

心磁信号广义S变换域奇异值分解滤波方法

针对心磁信号工频及背景噪声干扰问题, 提出了广义S变换奇异值分解(singular value decomposition, SVD)滤波方法.在离散S变换基础上, 导出了广义矩阵S变换和逆变换公式. 通过对采样信号进行广义S变换, 调节时频分辨率, 利用SVD分解方法确定有效心磁信 号区域, 实现自适应时频滤波. 实验结果表明, 该方法能有效滤除工频及背景噪声干 扰, 且在较少奇异值个数情况下可获得更好的滤波性能. 关键词： 心磁信号 S变换 奇异值分解 时频滤波     

基于奇异值分解对中国夏季降水模式误差订正的研究

利用奇异值分解(SVD)方法对国家气候中心气候业务模式CGCM的预报结果进行订正, 进而得到改进后的预报结果. 通过对1983–2011年中国夏季降水的模式预报和实际降水值各年份之间的耦合场进行SVD分解, 选取模式预报和实况降水相关性最好的前3–7个模态, 对这5种不同模态个数的订正结果加以对比, 选出对中国区域订正效果最好的模态个数, 得到模式预报的订正结果. 对2004–2009年6年进行交叉回报试验, 以距平相关系数和均方根误差作为评判标准来检验回报结果, 得出2004–2009大部分年份取前5个模态作为当年订正的模态个数时,订正效果最好. 利用已有的2004–2009年的模式和实际降水资料进行检验, 证实在大部分年份5个模态订正效果最好, 并将结果与系统误差订正法的结果相比较, 表明SVD法对2004–2009年 6年的订正结果中, 有4年比系统误差法的订正效果好. 以2010年作为预测年, 以1983–2009年27年交叉回报检验的结果确定模态个数, 对预测结果加以分析, 显示该方法具有潜在的业务应用价值. 关键词： 奇异值分解 模式预报订正 汛期降水     

基于主元分析与动态时间弯曲的故障诊断方法及应用研究

轴承是工程实际中常用而又极易损坏的部件,特别是对其早期微弱响应的辨识,具有重要的社会价值和意义。为提高运转轴承的安全可靠性和可维护性,提出了基于主元分析与动态时间弯曲距离的故障诊断方法,它可以准确对早期微弱动态响应辨识、诊断。该方法首先将典型故障样本信号与待测信号小波去噪并EMD分解,并对若干固有模态分量主元分析求取主元,然后对主元分量进行分析,获得相关特征值组成特征向量,计算待测信号与已知故障样本信号特征向量的弯曲距离,弯曲距离越小表明两信号越相似,从而辨识故障。此外,还可将其应用于转子、碰磨、齿轮故障诊断中,工程应用实例表明该方法可以准确故障分类,高效故障诊断。     

基于SVD的超精密工件自寻位加工算法能力评价

为进一步改善超精密表面修形的最终精度、效率与成本,优化超精密自寻位加工的工艺方向与工艺决策过程, 开展了对超精密工件的自寻位加工算法点云融合过程的定量评价研究,提出了基于SVD的自寻位加工算法能力评价方法。首先基于运动学方法建立了点云融合的矩阵表示,分别对平动、转动、复合运动等情况建立了自寻位结果的转换矩阵表示,获得自寻位点云融合转换矩阵;进而对转换矩阵进行奇异值分解得到转换矩阵的奇异值列表;最后将列表中最大奇异值用以表征自寻位加工算法的能力。通过对某型超精密叶片在平动、转动和复合运动、共计1078组自由放置状态进行分析,发现所提出的评价指标在独立平动和独立转动两种任意放置情况下能够正确地表征自寻位加工算法的工艺能力。对于独立平动情况,自寻位加工算法能够正常定位加工,其最大奇异值也与预设偏差较小;对于独立转动情况,当旋转角度小于45°时,均能够正确地进行自寻位加工,最大奇异值差值也趋近于零,旋转角度超过45°时,算法的自寻位加工能力恶化,这一特性能够被所提指标正确捕捉。对于由平动和转动构成的复合运动而言,所提指标显示约35%的情况能够正确进行自寻位加工,其余情况无法进行正确的自寻位加工。结果表明本文所提方法建立的指标能够正确表征自寻位加工算法能力。     

一种基于简化正交距离的近红外异常光谱判断方法

及时发现并剔除异常光谱对于提高近红外光谱分析的可靠性具有重要意义。首先介绍了基于正交距离的稳健主成分分析法判断异常光谱的原理,分析了该方法的局限性,在此基础上提出了一种基于简化正交距离的异常光谱判断方法,即以高浓度样品的光谱直接估计第一稳健主成分,再通过重复测量估计正交距离的统计参数来判断异常光谱。最后,采用上述两种方法对葡萄糖水溶液和2% Intralipid仿体溶液透射实验中受温度影响的异常光谱进行了判别。结果表明,基于正交距离的稳健主成分分析法,当崩溃值设定为40%时,葡萄糖水溶液和仿体溶液实验中受温度影响的异常光谱均能被正确识别;当崩溃值设定为25%时,对葡萄糖水溶液和仿体溶液实验中受温度影响的异常光谱漏判率分别为54.5%和72.7%。而简化正交距离法可以准确识别出葡萄糖水溶液和仿体溶液实验中受温度干扰的异常光谱,且具有无需预先设定崩溃值和测量持续时间较短等优点。因此,简化正交距离法在实际应用中相比基于正交距离的稳健主成分分析法有着显著的优势。     

An improved quantum principal component analysis algorithm based on the quantum singular threshold method

Quantum principal component analysis (qPCA) is a dimensionality reduction algorithm for getting the eigenvectors corresponding to top several eigenvalues of the data matrix and then reconstructing. However, qPCA can only construct the quantum state contains all the eigenvectors and eigenvalues. In this paper, we present an improved quantum principal component analysis (Improved qPCA) algorithm with a fixed threshold. We can reduce the singular value less than the threshold to 0 and obtain a target quantum state which can be used to get an output similar to qPCA after phase estimation. Compared with qPCA, our algorithm has only the target eigenvalues and the probability that we get each target eigenvalue is greater. Furthermore, our algorithm can serve as an additional regularization method and a subroutine for subsequent data processing.     

Research on the procedure for analyzing the sound quality contribution of sound sources and its application

Transfer path analysis (TPA) plays an important role for identifying and quantifying the contribution by airborne and structure-borne in the automotive industry. The main bottleneck of the TPA method is the test time consumption and complex procedure. It becomes a key target in many applications to find out the source with dominant contribution to overall noise rather than to identify each source. In recent years the contribution pattern of sources to the vehicle overall interior noise has changed with the reduction of engine noise, which masks all other sources. The panel radiation noise of vehicle body could not be ignored. There is an increasing demand for analyzing the sound quality contribution of sound sources in simple ways. The procedure for analyzing sound quality contribution of panel radiation noise is suggested in this study, in which an operational path analysis (OPA) method combined with partial singular value decomposition (PSVD) analysis is applied and sound quality objective assessment is introduced. The experimental research for verifying the procedure is finished, from which the source with largest sound quality contribution is picked up from three sources. For engineering application, the sound quality contributions of panels to the interior noise of a micro commercial vehicle are analyzed by using the procedure. By investigating the contributions of sound sources to each sound quality attribute, the dominant sound source is determined.     

A reference agent model for DCE MRI can be used to quantify the relative vascular permeability of two MRI contrast agents

Dynamic Contrast Enhancement (DCE) MRI has been used to measure the kinetic transport constant, K^trans, which is used to assess tumor angiogenesis and the effects of anti-angiogenic therapies. Standard DCE MRI methods must measure the pharmacokinetics of a contrast agent in the blood stream, known as the Arterial Input Function (AIF), which is then used as a reference for the pharmacokinetics of the agent in tumor tissue. However, the AIF is difficult to measure in pre-clinical tumor models and in patients. Moreover the AIF is dependent on the Fahraeus effect that causes a highly variable hematocrit (Hct) in tumor microvasculature, leading to erroneous estimates of K^trans. To overcome these problems, we have developed the Reference Agent Model (RAM) for DCE MRI analyses, which determines the relative K^trans of two contrast agents that are simultaneously co-injected and detected in the same tissue during a single DCE-MRI session. The RAM obviates the need to monitor the AIF because one contrast agent effectively serves as an internal reference in the tumor tissue for the other agent, and it also eliminates the systematic errors in the estimated K^trans caused by assuming an erroneous Hct. Simulations demonstrated that the RAM can accurately and precisely estimate the relative K^trans (R^Ktrans) of two agents. To experimentally evaluate the utility of RAM for analyzing DCE MRI results, we optimized a previously reported multiecho ¹⁹F MRI method to detect two perfluorinated contrast agents that were co-injected during a single in vivo study and selectively detected in the same tumor location. The results demonstrated that RAM determined R^Ktrans with excellent accuracy and precision.     

基于三维元胞模型的刻蚀工艺表面演化方法

为了更好地理解和认识刻蚀机理, 并为制造工艺提供优化指导, 采用三维元胞模型研究了刻蚀工艺的表面演化过程, 并着重探讨了离子对表面演化过程的影响.针对刻蚀离子入射角度的求解问题, 提出了一种降维分量拟合方法, 将一个三维曲面拟合问题转化为两个二维曲线拟合进行求解, 对入射点的表面法向量计算实现了快速求解, 与采用最小二乘多项式曲面拟合求解离子入射角度相比, 其计算精度和效率都有较大的提高; 对用于拟合计算的表面元胞的选取方法进行了改进, 提高了拟合的准确度.将这种方法应用到硅刻蚀工艺三维仿真中, 其模拟结果与相关实验结果对比, 验证了该方法对刻蚀工艺描述的有效性. 关键词： 刻蚀 三维元胞模型 表面演化算法 降维分量拟合     

Hybrid magnetic field formulation based on the losses separation method for modified dynamic inverse Jiles-Atherton model

Dynamic formulation based on the losses separation method in conducting media for the inverse Jiles-Atherton model is proposed. This formulation is based on the concept of the Hybrid Magnetic Field model (HMF). The HMF consists of the modification of the effective field by introducing two counter-fields associated, respectively, with the eddy current and excess losses. Such a formulation is characterized by seven parameters with five parameters issued from the quasi-static Jiles-Atherton model. Thus, two new parameters related to these fields are added to that defined in the quasi-static model. The identification of these new parameters is based on the measurements of the volumetric energy density. To validate this formulation, measurements are carried out on grain non-oriented Fe-Si 3% electrical sheets.     

A method for extracting human gait series from accelerometer signals based on the ensemble empirical mode decomposition

In this paper,the ensemble empirical mode decomposition(EEMD) is applied to analyse accelerometer signals collected during normal human walking.First,the self-adaptive feature of EEMD is utilised to decompose the accelerometer signals,thus sifting out several intrinsic mode functions(IMFs) at disparate scales.Then,gait series can be extracted through peak detection from the eigen IMF that best represents gait rhythmicity.Compared with the method based on the empirical mode decomposition(EMD),the EEMD-based method has the following advantages:it remarkably improves the detection rate of peak values hidden in the original accelerometer signal,even when the signal is severely contaminated by the intermittent noises;this method effectively prevents the phenomenon of mode mixing found in the process of EMD.And a reasonable selection of parameters for the stop-filtering criteria can improve the calculation speed of the EEMD-based method.Meanwhile,the endpoint effect can be suppressed by using the auto regressive and moving average model to extend a short-time series in dual directions.The results suggest that EEMD is a powerful tool for extraction of gait rhythmicity and it also provides valuable clues for extracting eigen rhythm of other physiological signals.