Segmentation of ultrasound images of the carotid using RANSAC and cubic splines

A new algorithm is proposed for the semi-automatic segmentation of the near-end and the far-end adventitia boundary of the common carotid artery in ultrasound images. It uses the random sample consensus method to estimate the most significant cubic splines fitting the edge map of a longitudinal section. The consensus of the geometric model (a spline) is evaluated through a new gain function, which integrates the responses to different discriminating features of the carotid boundary: the proximity of the geometric model to any edge or to valley shaped edges; the consistency between the orientation of the normal to the geometric model and the intensity gradient; and the distance to a rough estimate of the lumen boundary.A set of 50 longitudinal B-mode images of the common carotid and their manual segmentations performed by two medical experts were used to assess the performance of the method. The image set was taken from 25 different subjects, most of them having plaques of different classes (class II to class IV), sizes and shapes.The quantitative evaluation showed promising results, having detection errors similar to the ones observed in manual segmentations for 95% of the far-end boundaries and 73% of the near-end boundaries.     

多元散射校正与Savitzky-Golay平滑模式的组合优选应用于土壤有机质的近红外光谱分析

采用近红外(NIR)漫反射光谱,建立土壤有机质的NIR光谱分析的偏最小二乘(PLS)模型,比较和选择多元散射校正(MSC)和Savitzky-Golay(SG)平滑用于改善NIR光谱分析的预测能力。把SG平滑模式由原来的117种扩充为483种,并构建了SG平滑模式与PLS因子数联合优选的化学计量学平台。对于单独(或联合)做MSC、SG平滑预处理以及未做光谱预处理的5种情形,分别建立土壤有机质NIR光谱分析的PLS模型。最优的情形是先后做SG平滑和MSC预处理,其中最优的SG平滑参数为5次多项式、3阶导数、21点平滑,对应的PLS因子数、预测均方根偏差(RMSEP)、预测相关系数(R_p)分别为5,0.246(%),0.883,大幅度优于未做光谱预处理的模型预测效果。从而表明,SG平滑和MSC的组合优选可以显著改善土壤有机质的NIR分析效果。所构建的化学计量学平台和方法框架是改善NIR分析能力的有效途径。     

Dividing Cubes算法生成的物体表面的法向量方向的光顺操作

在用DividingCubes算法提取的边界体素所构造的物体表面上,可能会存在法向量方向突变,使得物体表面光照图显示粗糙,文中提出了一种的领域加权平均法,对物体表面的法向量方向进行光顺处理,光顺操作只在相关边界体素间进行,并且对有多个等值面交汇的边界体素将不进行光顺操作,以避免模糊位于多个区域处的边界和保持物体表面光照图的细节,为避免在屏幕上产生孔洞,用光线投射法显示物体表面,文中所采用的光顺操作可以消除物体表面的法向量方向突变,使物体表面光照图光谱细腻,最后,给出一个医学图像的测试实例。     

固定区间Kalman平滑新算法

用现代时间序列分析方法,基于ＡＲＭＡ新息模型和白噪声估值器,提出了一种正向固定区间稳态Ｋａｌｍａｎ平滑新算法和两种反向固定区间稳态Ｋａｌｍａｎ平滑新算法,并给出了保证算法最优性的最优初值公式。算法简单,便于实时应用。仿真例子说明了它们的有效性。     

Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter

The time aggregation properties of the Hodrick-Prescott (HP) filter, which decomposes a time series into trend and cycle, are analyzed for the case of annual, quarterly, and monthly data. Aggregation of the disaggregate components cannot be obtained as the exact result from direct application of an HP filter to the aggregate series. Employing several criteria, HP decompositions for different levels of aggregation that provide similar results can be found. The aggregation is guided by the principle that the period associated with the frequency for which the filter gain is should not be altered. This criterion is intuitive and easy to apply. It is shown that it is approximated, to the first order, by an already proposed empirical rule and that alternative, more complex criteria yield similar results. Moreover, the values of the smoothing parameter of the HP filter that provide results which are approximately consistent under aggregation are considerably robust with respect to the ARIMA model of the series. Aggregation is found to perform better for the case of temporal aggregation than for systematic sampling. The desirability of exact aggregation consistency is investigated. A clarification concerning the supposed spuriousness of the cycles obtained by the HP filter is discussed.     

基于五点三次平滑算法的入库 流量反推研究

由于受水库枢纽工程的影响,使得反推计算入库流量本身存在较大误差,从而增加了水库洪水预报模型研制的难度。通过对广西多个水电厂洪水预报实践,对入库洪水预报存在误差的原因进行了分析,提出使用五点三次平滑算法对入库流量进行反推,用以指导实时预报。     

A non-monotone inexact regularized smoothing Newton method for solving nonlinear complementarity problems

In the paper [S.P. Rui and C.X. Xu, A smoothing inexact Newton method for nonlinear complementarity problems, J. Comput. Appl. Math. 233 (2010), pp. 2332–2338], the authors proposed an inexact smoothing Newton method for nonlinear complementarity problems (NCP) with the assumption that F is a uniform P function. In this paper, we present a non-monotone inexact regularized smoothing Newton method for solving the NCP which is based on Fischer–Burmeister smoothing function. We show that the proposed algorithm is globally convergent and has a locally superlinear convergence rate under the weaker condition that F is a P ₀ function and the solution of NCP is non-empty and bounded. Numerical results are also reported for the test problems, which show the effectiveness of the proposed algorithm.     

改进D-P算法在图像轮廓平滑中的应用

针对传统D-P算法速度较慢、编程不方便的问题,提出一种改进算法。以一定步长对轮廓进行遍历,根据轮廓上点到所选轮廓段首末点连线最大距离与距离阈值的大小关系,按轮廓遍历顺序获取曲线轮廓的特征点,并在相邻的特征点之间采用贝塞尔曲线进行平滑。实验结果表明,改进算法的速度比传统算法提高10%以上。     

绝对值方程研究进展

线性规划、二次规划、双矩阵对策等问题都能转化为线性互补问题,而线性互补问题又可以归结为绝对值方程,因此研究绝对值方程具有重要的意义。绝对值方程是一个NP-hard问题,对绝对值方程的研究现状进行了分析,给出了绝对值方程的理论研究现状,总结了绝对值方程的若干求解算法。这些算法可以归结为三类：1）逐次线性化方法,2）半光滑牛顿法,3）光滑牛顿法。指出解的存在性、构造光滑函数、采用智能算法求解以及算法收敛性分析将成为绝对值方程的研究热点。     

基于凸集论的稠密视差图优化算法

针对计算机视觉领域中立体匹配算法在图像无纹理区产生的误匹配问题,提出以全变差函数为凸约束集,使用次梯度投影法,对通过初始视差变换后的立体图像对之间的像素误差函数和视差二次平滑因子形成的严格凸函数进行求解,寻求立体图像对之间的最优视差图。实验结果表明,该方法不仅能保留初始视差图的边缘,而且减少了由先前立体匹配算法求得的视差图在无纹理区产生的误匹配点,取得了良好的视差图优化效果。