检索结果-内蒙古大学图书馆

Automatic Segmentation of 3-D Brain MR Images by Using Global Tissue Spatial Structure Information

IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY 2014年第5期24卷 1-5页

作者： Liu, Xiaoyun Chen, Fen Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 611731 Peoples R China

Segmentation of brain tissues from MR images is medically valuable for helping to assess many diseases. In this paper, we propose a three-layer Gaussian mixture model framework (3L-GMM) for fully automatic tissue segmentation of three-dimensional brain MR images by using spatial structure information. It uses separate GMMs to model the intensity information, the spatial structure information, and the intensity-spatial feature vector, respectively. We implement the brain tissues segmentation task by maximizing the a posteriori probability of the 3L-GMM model. Experiments are conducted on the threedimensional, T1-weighted, simulated and in vivo MR images of the BrainWeb and IBSR data sets. The qualitative and quantitative comparisons with the gold standard demonstrate that the proposed model can achieve performance improvement over the state-of-the-art methods in the literature.

关键词： expectation maximization algorithm Gaussian mixture model (GMM) image segmentation magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Estimation of vector error correction models with mixed-frequency data

引用

JOURNAL OF TIME SERIES ANALYSIS 2013年第2期34卷 194-205页

作者： Seong, Byeongchan Ahn, Sung K. Zadrozny, Peter A. Chung Ang Univ Seoul 156756 South Korea Washington State Univ Pullman WA 99164 USA US Bur Labor Stat Washington DC 20212 USA

Vector autoregressive (VAR) models with error-correction structures (VECMs) that account for cointegrated variables have been studied extensively and used for further analyses such as forecasting, but only with single-frequency data. Both unstructured and structured VAR models have been estimated and used with mixed-frequency data. However, VECMs have not been studied or used with mixed-frequency data. The article aims partly to fill this gap by estimating a VECM using the expectation-maximization (EM) algorithm and US data on four monthly coincident indicators and quarterly real GDP and, then, using the estimated model to compute in-sample monthly smoothed estimates and out-of-sample monthly forecasts of GDP. Because the model is treated as operating at the highest monthly frequency and the monthly-quarterly data are used as given (neither interpolated to all-monthly data, nor aggregated to all-quarterly data), the application is expected to be unbiased and efficient. A Monte Carlo analysis compares the accuracy of VECMs estimated with the given mixed-frequency data vs. with their single-frequency temporal aggregate.

关键词： Missing data cointegration state-space model Kalman filter expectation maximization algorithm smoothing C13 C22 C32

来源：评论

学校读者我要写书评

暂无评论

Adjustment models for multivariate geodetic time series with vector-autoregressive errors

引用

JOURNAL OF APPLIED GEODESY 2021年第3期15卷 243-267页

作者： Kargoll, Boris Dorndorf, Alexander Omidalizarandi, Mohammad Paffenholz, Jens-Andre Alkhatib, Hamza Anhalt Univ Appl Sci Inst Geoinformat & Surveying Seminarpl 2a D-06846 Dessau Rosslau Germany Leibniz Univ Hannover Geodet Inst Nienburger Str 1 D-30167 Hannover Germany Tech Univ Clausthal Inst Geoengn Erzstr 18 D-38678 Clausthal Zellerfeld Germany

In this contribution, a vector-autoregressive (VAR) process with multivariate t-distributed random deviations is incorporated into the Gauss-Helmert model (GHM), resulting in an innovative adjustment model. This model is versatile since it allows for a wide range of functional models, unknown forms of auto- and cross-correlations, and outlier patterns. Subsequently, a computationally convenient iteratively reweighted least squares method based on an expectation maximization algorithm is derived in order to estimate the parameters of the functional model, the unknown coefficients of the VAR process, the cofactor matrix, and the degree of freedom of the t-distribution. The proposed method is validated in terms of its estimation bias and convergence behavior by means of a Monte Carlo simulation based on a GHM of a circle in two dimensions. The methodology is applied in two different fields of application within engineering geodesy: In the first scenario, the offset and linear drift of a noisy accelerometer are estimated based on a Gauss-Markov model with VAR and multivariate t-distributed errors, as a special case of the proposed GHM. In the second scenario real laser tracker measurements with outliers are adjusted to estimate the parameters of a sphere employing the proposed GHM with VAR and multivariate t-distributed errors. For both scenarios the estimated parameters of the fitted VAR model and multivariate t-distribution are analyzed for evidence of auto- or cross-correlations and deviation from a normal distribution regarding the measurement noise.

关键词： Gauss-Helmert model Gauss-Markov model vector-autoregressive model auto-correlations cross-correlations multivariate t-distribution iteratively reweighted least squares expectation maximization algorithm accelerometer time series

来源：评论

学校读者我要写书评

暂无评论

Likelihood inference for COM-Poisson cure rate model with interval-censored data and Weibull lifetimes

引用

STATISTICAL METHODS IN MEDICAL RESEARCH 2017年第5期26卷 2093-2113页

作者： Pal, Suvra Balakrishnan, N. Univ Texas Arlington Dept Math Arlington TX 76019 USA McMaster Univ Dept Math & Stat Hamilton ON Canada

In this paper, we consider a competing cause scenario and assume the number of competing causes to follow a Conway-Maxwell Poisson distribution which can capture both over and under dispersion that is usually encountered in discrete data. Assuming the population of interest having a component cure and the form of the data to be interval censored, as opposed to the usually considered right-censored data, the main contribution is in developing the steps of the expectation maximization algorithm for the determination of the maximum likelihood estimates of the model parameters of the flexible Conway-Maxwell Poisson cure rate model with Weibull lifetimes. An extensive Monte Carlo simulation study is carried out to demonstrate the performance of the proposed estimation method. Model discrimination within the Conway-Maxwell Poisson distribution is addressed using the likelihood ratio test and information-based criteria to select a suitable competing cause distribution that provides the best fit to the data. A simulation study is also carried out to demonstrate the loss in efficiency when selecting an improper competing cause distribution which justifies the use of a flexible family of distributions for the number of competing causes. Finally, the proposed methodology and the flexibility of the Conway-Maxwell Poisson distribution are illustrated with two known data sets from the literature: smoking cessation data and breast cosmesis data.

关键词： Long-term survival model maximum likelihood estimate expectation maximization algorithm profile likelihood likelihood ratio test Akaike information criterion Bayesian information criterion

来源：评论

学校读者我要写书评

暂无评论

Saddlepoint approximations for rank-invariant permutation tests and confidence intervals with interval-censoring

引用

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 2014年第2期42卷 308-324页

作者： Abd-Elfattah, Ehab Butler, Ronald Ain Shams Univ Fac Educ Dept Math Cairo Egypt So Methodist Univ Dallas TX 75275 USA

Interval-censored data occur when subjects are assessed by using regular follow-up. In such instances, we consider rank-invariant permutation tests to test the significance of a treatment versus a control. For a wide class of such tests, which includes the Peto & Peto class, we present saddlepoint approximations for the exact permutation mid-P-values which achieve extremely small relative errors. The speed and stability of these saddlepoint computations make them practicable for inverting the permutation tests and we compute nominal 100(1-)% confidence intervals for the treatment effect. Such confidence intervals are of substantial clinical importance since, more than simply stating the level of statistical significance, they quantify the significant benefit of the treatment by providing a confidence interval for the percentage increase in mean (or median) treatment survival time as compared to control. Our methodology makes heavy use of nonparametric MLEs (NPMLEs) for survival functions and some limitations of existing algorithms, such as the hybrid ICM algorithm, are noted and accommodated. The Canadian Journal of Statistics 42: 308-324;2014 (c) 2014 Statistical Society of Canada ResumeLes donnees obtenues lorsque des sujets sont evalues lors de visites regulieres sont souvent censurees par intervalle. Dans de telles circonstances, les auteurs etudient des tests de permutation invariants aux transformations preservant les rangs pour tester la significativite d'un traitement par rapport au controle. Pour une large classe de tests, incluant la classe de Peto & Peto, ils proposent des approximations en point de selle pour le p-value central qui presentent une erreur relative tres faible. La vitesse et la stabilite du calcul de ces p-value centraux de permutation en font une methode applicable pour inverser les tests de permutation et en tirer des intervalles de confiance a 100(1-)% pour la taille de l'effet du traitement. D'une importance clinique incontestable, de t

关键词： expectation maximization algorithm interval censoring iterative convex minorant algorithm permutation test saddlepoint approximation two-sample test

来源：评论

学校读者我要写书评

暂无评论

Embryo zebrafish segmentation using an improved hybrid method

引用

JOURNAL OF MICROSCOPY 2013年第1期250卷 68-75页

作者： Wu, Tao Lu, Jianfeng Lu, Yanting Liu, Tianming Yang, Jingyu Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China Univ Georgia Dept Comp Sci Athens GA 30602 USA

Zebrafish is an invaluable vertebrate model in life science research and has been widely used in biological pathway analysis, molecular screening and disease modelling, among others. As a result, microscopic imaging has become an essential step in zebrafish phenotype analysis, and image segmentation thus plays an important role in the zebrafish microscopy analysis. Due to the nonuniform distribution of intensity and weak boundary in zebrafish microscope images, the traditionally used segmentation methods may lead to unsatisfactory result. Here, a novel hybrid method that integrates region and boundary information into active contour model is proposed to segment zebrafish embryos from the background, which performs better than traditional segmentation models. Meanwhile, how to utilize the gradient information effectively in image segmentation is still an open problem. In this paper, we propose to improve the aforementioned hybrid method in two aspects. Firstly, the mean grey value of background is estimated by the expectation maximization (EM) algorithm to constrain the active curve evolution. Secondly, an edge stopping function sensitive to gradient information is designed to stop curve evolution when the active curve reaches the embryo boundary. Experimental results show that the proposed methods can provide superior segmentation results compared to existing algorithms.

关键词： Active contour model edge stopping function expectation maximization algorithm image segmentation zebrafish embryo image

来源：评论

学校读者我要写书评

暂无评论

Dynamics in cryo EM reconstructions visualized with maximum-likelihood derived variance maps

引用

JOURNAL OF STRUCTURAL BIOLOGY 2013年第3期181卷 195-206页

作者： Wang, Qiu Matsui, Tsutomu Domitrovic, Tatiana Zheng, Yili Doerschuk, Peter C. Johnson, John E. Cornell Univ Ithaca NY 14853 USA Scripps Res Inst Dept Mol Biol Menlo Pk CA 94025 USA SLAC Natl Accelerator Lab Stanford Synchrotron Radiat Lightsource Menlo Pk CA 94025 USA Scripps Res Inst Dept Mol Biol La Jolla CA USA Purdue Univ W Lafayette IN 47907 USA

CryoEM data capture the dynamic character associated with biological macromolecular assemblies by preserving the various conformations of the individual specimens at the moment of flash freezing. Regions of high variation in the data set are apparent in the image reconstruction due to the poor density that results from the lack of superposition of these regions. These observations are qualitative and, to date, only preliminary efforts have been made to quantitate the heterogeneity in the ensemble of particles that are individually imaged. We developed and tested a quantitative method for simultaneously computing a reconstruction of the particle and a map of the space-varying heterogeneity of the particle based on an entire data set. The method uses a maximum likelihood algorithm that explicitly takes into account the continuous variability from one instance to another instance of the particle. The result describes the heterogeneity of the particle as a variance to be plotted at every voxel of the reconstructed density. The test, employing time resolved data sets of virus maturation, not only recapitulated local variations obtained with difference map analysis, but revealed a remarkable time dependent reduction in the overall particle dynamics that was unobservable with classical methods of analysis. (c) 2012 Elsevier Inc. All rights reserved.

关键词： Time-resolved Single particle reconstruction Virus maturation Protein folding Quasi equivalence Cryo electron microscopy Nudaurelia Capensis Omega Virus Maximum likelihood estimation expectation maximization algorithm Heterogeneous particles Variance map

来源：评论

学校读者我要写书评

暂无评论

Finite mixture of varying coefficient model: Estimation and component selection

引用

JOURNAL OF MULTIVARIATE ANALYSIS 2019年 171卷 452-474页

作者： Ye, Mao Lu, Zhao-Hua Li, Yimei Song, Xinyuan Purdue Univ Dept Stat 610 Purdue Mall W Lafayette IN 47907 USA St Jude Childrens Res Hosp Dept Biostat MS 768262 Danny Thomas Pl Memphis TN 38105 USA Chinese Univ Hong Kong Shenzhen Res Inst Shatin Hong Kong Peoples R China Chinese Univ Hong Kong Dept Stat Shatin Hong Kong Peoples R China

Heterogeneous longitudinal data have become prevalent in medical, biological, and social studies. This paper proposes a finite mixture of varying coefficient models for handling heterogeneous populations. Each component of the mixture is modeled by a varying coefficient mixed-effect model that characterizes the longitudinal relations among variables. The identifiability of the mixture model is studied. Regression splines with equally spaced knots are used to approximate the varying coefficient functions, and a nested expectation maximization algorithm is developed to obtain the maximum likelihood estimation. We propose a penalized likelihood method based on the smoothly clipped absolute deviation (SCAD) penalty for the component selection of finite mixture of varying coefficient model. A modified BIC-based criterion based on the SCAD penalty, the BICSCAD, is proposed for selecting the penalty parameter and spline space simultaneously. The asymptotic properties of parameter estimation and component selection consistency are studied under mild conditions. Simulation studies are conducted to illustrate the component selection, parameter estimation, and inference of the proposed method. The model is then applied to a heterogeneous longitudinal data set from a study of the treatment effect on the use of heroin in the California Civil Addict Program. (C) 2019 Elsevier Inc. All rights reserved.

关键词： expectation maximization algorithm Finite mixture model Model selection Random effects SCAD Varying coefficients

来源：评论

学校读者我要写书评

暂无评论

Detecting DNA regulatory motifs by incorporating positional trends in information content

引用

GENOME BIOLOGY 2004年第7期5卷 1-21页

作者： Kechris, KJ van Zwet, E Bickel, PJ Eisen, MB Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA Univ Calif Berkeley Lawrence Berkeley Lab Div Life Sci Dept Genome Sci Berkeley CA 94720 USA Univ Calif Berkeley Dept Mol & Cell Biol Ctr Integrat Genom Berkeley CA 94720 USA

On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods. We assign position-specific prior distributions to the frequency parameters of the model, penalizing deviations from a specified conservation profile. Examples with both simulated and real data show that this extension helps discover motifs as the data become noisier or when there is a competing false motif.

关键词： Prior Distribution Change Point Transcription Factor Binding Site Additional Data File expectation maximization algorithm

来源：评论

学校读者我要写书评

暂无评论

4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening

引用

JOURNAL OF CHEMINFORMATICS 2011年第1期3卷 1-17页

作者： Jahn, Andreas Rosenbaum, Lars Hinselmann, Georg Zell, Andreas Univ Tubingen Ctr Bioinformat Tubingen ZBIT D-72076 Tubingen Germany

Background: The performance of 3D-based virtual screening similarity functions is affected by the applied conformations of compounds. Therefore, the results of 3D approaches are often less robust than 2D approaches. The application of 3D methods on multiple conformer data sets normally reduces this weakness, but entails a significant computational overhead. Therefore, we developed a special conformational space encoding by means of Gaussian mixture models and a similarity function that operates on these models. The application of a model-based encoding allows an efficient comparison of the conformational space of compounds. Results: Comparisons of our 4D flexible atom-pair approach with over 15 state-of-the-art 2D- and 3D-based virtual screening similarity functions on the 40 data sets of the Directory of Useful Decoys show a robust performance of our approach. Even 3D-based approaches that operate on multiple conformers yield inferior results. The 4D flexible atom-pair method achieves an averaged AUC value of 0.78 on the filtered Directory of Useful Decoys data sets. The best 2D- and 3D-based approaches of this study yield an AUC value of 0.74 and 0.72, respectively. As a result, the 4D flexible atom-pair approach achieves an average rank of 1.25 with respect to 15 other state-of-the-art similarity functions and four different evaluation metrics. Conclusions: Our 4D method yields a robust performance on 40 pharmaceutically relevant targets. The conformational space encoding enables an efficient comparison of the conformational space. Therefore, the weakness of the 3D-based approaches on single conformations is circumvented. With over 100,000 similarity calculations on a single desktop CPU, the utilization of the 4D flexible atom-pair in real-world applications is feasible.

关键词： Virtual Screening expectation maximization algorithm Conformational Space Optimal Assignment Conformational Ensemble

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：