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Vascular Tree Segmentation in Medical images Using Hessian-Based Multiscale Filtering and Level Set Method

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2013年第1期2013卷 502013页

作者： Jin, Jiaoying Yang, Linjun Zhang, Xuming Ding, Mingyue Huazhong Univ Sci & Technol Dept Biomed Engn Sch Life Sci & TechnolEduc Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

Vascular segmentation plays an important role in medical image analysis. A novel technique for the automatic extraction of vascular trees from 2D medical images is presented, which combines Hessian-based multiscale filtering and a modified level set method. In the proposed algorithm, themorphological top-hat transformation is firstly adopted to attenuate background. Then Hessian-based multiscale filtering is used to enhance vascular structures by combining Hessian matrix with Gaussian convolution to tune the filtering response to the specific scales. Because Gaussian convolution tends to blur vessel boundaries, which makes scale selection inaccurate, an improved level set method is finally proposed to extract vascular structures by introducing an external constrained term related to the standard deviation of Gaussian function into the traditional level set. Our approach was tested on synthetic images with vascular-like structures and 2D slices extracted from real 3D abdomen magnetic resonance angiography (MRA) images along the coronal plane. The segmentation rates for synthetic images are above 95%. The results for MRA images demonstrate that the proposed method can extract most of the vascular structures successfully and accurately in visualization. Therefore, the proposed method is effective for the vascular tree extraction in medical images.

关键词： Numerical methods

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Multistability of Two Kinds of Recurrent Neural Networks With Activation Functions Symmetrical About the Origin on the Phase Plane

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2013年第11期24卷 1749-1762页

作者： Zeng, Zhigang Zheng, Wei Xing Univ Western Sydney Sch Comp Engn & Math Sydney NSW 2751 Australia Minist China Key Lab Image Proc & Intelligent Control Educ Wuhan 430074 Peoples R China

In this paper, we investigate multistability of two kinds of recurrent neural networks with time-varying delays and activation functions symmetrical about the origin on the phase plane. One kind of activation function is with zero slope at the origin on the phase plane, while the other is with nonzero slope at the origin on the phase plane. We derive sufficient conditions under which these two kinds of n-dimensional recurrent neural networks are guaranteed to have (2m + 1)(n) equilibrium points, with (m + 1)(n) of them being locally exponentially stable. These new conditions improve and extend the existing multistability results for recurrent neural networks. Finally, the validity and performance of the theoretical results are demonstrated through two numerical examples.

关键词： Attractive set equilibrium point multistability time-varying delays

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Pixel-wise decay parameter adaption for nonlocal means image denoising

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JOURNAL OF ELECTRONIC IMAGING 2013年第4期22卷

作者： Zhan, Yi Ding, Mingyue Zhang, Xuming Huazhong Univ Sci & Technol Sch Life Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist ChinaDept Biomed Engn Wuhan 430074 Peoples R China

The globally fixed decay parameter is generally adopted in the traditional nonlocal means method for similarity computation, which has a negative influence on its restoration performance. To address this problem, we propose to adaptively tune the decay parameter for each image pixel using the golden section search method based on the pixel-wise minimum mean square error, which can be estimated using the prefiltered result and the estimated noise component. The quantitative and subjective comparisons of restoration performance among the proposed method and several state-of-the-art methods indicate that it can achieve a better performance in noise reduction, artifact avoidance, and detail preservation. (C) 2013 SPIE and IS&T

关键词： image denoising Denoising Magnetic resonance imaging Error analysis image analysis Signal to noise ratio Surface plasmons Brain image processing Interference (communication)

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Stability Analysis and controller Design of Positive Linear Systems Subject to Actuator Saturation

Stability Analysis and Controller Design of Positive Linear ...

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第三十二届中国控制会议

作者： ZHANG Jishi Wu Yan WANG Yanwu GAO Zhonghu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Institute of Marine Electric Propulsion CSIC

ISBN: (纸本)9781479900305

This paper addresses the stability and stabilization problems for a class of positive linear systems in the presence of saturating *** objective is to give conditions of the stability,and design state feedback control laws such that the closed-loop systems is asymptotically stable and positive at the origin with a large domain of *** sufficient conditions for stabilization and positivity are derived via the Lyapunov functions method and convex analysis in both the continuous-time and the discrete-time cases,*** state feedback controller design and the estimation of domain of attraction are presented by solving a convex optimization problem with LMIs constraints.A numerical example is given to show the effectiveness of the proposed methods.

关键词： Actuator Saturation Stability Analysis Positive System Domain of Attraction

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MRPGA: Motif Detecting by Modified Random Projection Strategy and Genetic Algorithm

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JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2013年第5期10卷 1209-1214页

作者： Wang, Xun Song, Tao Wang, Zhongyu Su, Yansen Liu, Xueming Univ Tsukuba Grad Sch Syst & Informat Engn Tsukuba Ibaraki 3050006 Japan Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

Detecting common patterns or motifs in a set of DNA sequences is a major task in computational biology. Recently, this task was formally formulated as a planted (I, d)-motif problem, and several instances of the problem have been posed as challenges for motif detecting algorithms. In this work, an approach of genetic algorithm using Bayesian inference is proposed to identify (I, d)-motifs, where a modified random projection strategy is applied to generate a good initial population of the genetic algorithm. Based on our method, a program called MRPGA is developed, and experimental results on simulated data show that MRPGA performs better than Random Projection and GARPS in finding weak signal motifs. We test MRPGA on realistic biological data by identifying ERE binding sites of estradiol, CRP in Escherichia coli, as well as transcription factors in E2F family. In real-data applications, MRPGA achieves superior performances comparing with MEME, MDGA, BioProsceptor and BioOptimizor.

关键词： Motif Detection Random Projection Genetic Algorithm Bayesian Inference

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Face recognition algorithm based on improved facial model

Face recognition algorithm based on improved facial model

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International Conference on Natural Computation (ICNC)

作者： Chengyun Liu Zhenxue Chen Faliang Chang Kaifang Wang Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei P. R. China School of Control Science & Engineering Shandong University Jinan P. R. China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing P. R. China

ISBN: (纸本)9781479951529

Face recognition is one of typical biometric identification method, which has a great prospect in secure authentication system, file management, human-computer interaction and social security. This paper proposes gray-scale characteristics and creates facial templates to recognize faces method based on a given number of samples. Firstly, it selects the method of building template according to the number of samples to create the facial template image; then, it will compare the difference of first-order edge entropy between recognition image and the template image and find the best match result; finally, the recognition result is output. Experimental results show that the proposed algorithm has good recognition effect on face recognition under non-constraint conditions.

关键词： Face recognition Face Entropy Lighting image edge detection

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Event-triggered tracking control for heterogeneous multi-agent systems with Markov communication delays

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2013年第5期350卷 1312-1334页

作者： Yin, Xiuxia Yue, Dong Huazhong Univ Sci & Technol Dept Control Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Minist Educ Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this paper, we investigate the consensus problem of a set of discrete-time heterogeneous multi-agent systems with random communication delays represented by a Markov chain, where the multi-agent systems are composed of two kinds of agents differed by their dynamics. First, distributed consensus control is designed by employing the event-triggered communication technique, which can lead to a significant reduction of the information communication burden in the multi-agent network. Then, the mean square stability of the closed loop multi-agent systems is analyzed based on the Lyapunov functional method and the Kronecker product technique. Sufficient conditions are obtained to guarantee the consensus in terms of linear matrix inequalities (LMIs). Finally, a simulation example is given to illustrate the effectiveness of the developed theory. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： Multi agent systems

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L2-Gain analysis of event-triggered networked control systems: a discontinuous Lyapunov functional approach

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2013年第11期23卷 1277-1300页

作者： Hu, Songlin Yue, Dong Huazhong Univ Sci & Technol Dept Control Sci & Engn Minist Educ Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Wuhan 430074 Peoples R China

In this paper, the problems of exponential stability and L2-gain analysis of event-triggered networked control systems (NCSs) with network-induced delays are studied. We first propose event-triggering conditions in the sensor side and controller side, respectively. Because the implementation of our event-triggering scheme only needs periodic supervision of the system state at the constant sampling instants, instead of being monitored continuously, it is expected that the scheme will improve the resource utilization. Taking the network-induced delays into account and using delay system approach, we constructed a unified model of NCSs with hybrid event-triggering schemes. On the basis of this model, sufficient conditions for the exponential stability and L2-gain analysis are developed in the form of LMIs by using a discontinuous Lyapunov-Krasovskii functional approach. Moreover, the corresponding results can be further extended to more general cases, where the system matrices of the considered plant contain parameter uncertainties, represented in either polytopic or norm-bounded frameworks. In addition, as a special case, we also present the exponential stability, L2-gain analysis, and the control feedback gain design of event-triggered NCSs without considering the effects of network-induced delays and event-triggering condition in the controller side. Finally, a simulation example is provided to illustrate the usefulness and effectiveness of the proposed hybrid event-triggering *** (c) 2012 John Wiley & Sons, Ltd.

关键词： event-triggering exponential stability L2-gain Lyapunov-Krasovskii functional NCSs

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Passivity analysis for delayed discontinuous neural networks

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SOFT COMPUTING 2013年第11期17卷 2033-2041页

作者： Xiao, Jian Zeng, Zhigang Shen, Wenwen Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Hunan Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this paper, we have integrated the passivity of delayed neural networks with discontinuous activations which are unbounded. Based on differential inclusion theory and nonsmooth analysis, some sufficient conditions are presented by means of the generalized Lyapunov method. The results are established in form of linear matrix inequality. In addition, Some numerical examples are proposed to show the effectiveness of the developed results.

关键词： Discontinuous neuron activation Neural networks Passivity Differential inclusion

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Unsupervised color-texture segmentation based on multiscale quaternion Gabor filters and splitting strategy

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SIGNAL processing 2013年第9期93卷 2559-2572页

作者： Li, Lei Jin, Lianghai Xu, Xiangyang Song, Enmin Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Educ Minist Image Proc & Intelligent Control Key Lab Wuhan 430074 Peoples R China

This paper proposes a new method for color-texture segmentation based on a splitting framework with graph cut technique. To process the scale difference of quaternion Gabor filter (QGF) features of a color textured image, a new multiscale QGF (MQGF) is introduced to describe texture attributes of the given image. Then, the segmentation is formulated in terms of energy minimization gradually obtained using binary graph cuts, where color and MQGF features are modeled with a multivariate finite mixture model, and minimum description length (MDL) principle is integrated into this framework as a splitting criterion. In contrast to previous approaches, our method finds an optimal segmentation by balancing energy cost and coding length, and the segmentation result is determined during the splitting process automatically. Experimental results on both synthetic and real natural color textured images demonstrate the good performance of the proposed method. (c) 2013 Elsevier B.V. All rights reserved.

关键词： Color-texture segmentation Multiscale quaternion Gabor filter Graph cuts Minimum description length

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