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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

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2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011

作者： Hosseini, M. Parsa Soltanian-Zadeh, Hamid Akhlaghpoor, Shahram Department of Electrical Engineering Islamic Azad University Science and Research Branch of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs). © 2011 IEEE.

关键词： computerized tomography

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An application of fractional intelligent robust controller for electromechanical valve

An application of fractional intelligent robust controller f...

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2011 World Congress on Information and Communication Technologies, WICT 2011

作者： Banerjee, Tribeni Prasad Saha, Suman Das, Swagatam Abraham, Ajith Dept. of Electronics and Telecommunication Engineering Jadavpur University Kolkata 700 032 India CSIR-Central Mechanical Engineering Research Institute Drives and Control System Laboratory Durgapur-713209 West-Bengal India Scientific Network for Innovation and Research Excellence WA United States EU Center of Excellence Faculty of Electrical Engineering and Computer Science VSB - Technical University of Ostrava Czech Republic

ISBN: (纸本)9781467301251

The paper analyzed and model of a fault tolerant electromechanical controlled worm gear driven fuel shut off valve for aerospace application. The analysis is mainly on design a reduced order fractional controller. This is for controlling the velocity of worm gear so that the friction torque due to uneven rotational speed can be avoided. Because with the friction and stiction and backlash the valve system performance is reduced and more and more unstable this leads the system to failure. The proposed controller can provide robustness against the uncertain loading torque and system parameter. © 2011 IEEE.

关键词： controllers

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

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2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. © 2011 IEEE.

关键词： Pulmonary diseases

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Evaluation of functional connectivity in control and ADHD subjects by generalized Canonical Correlation and Probabilistic Independent Component Analysis

Evaluation of functional connectivity in control and ADHD su...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： AmirEhsan Lashkari Hamid Soltanian-Zadeh GholamAli Hosseinzadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA

Functional connectivity can be evaluated by temporal correlation between spatial neurophysiologic events or correlation between neural activities of brain regions. Unlike anatomical connectivity which represents physical connections between two brain regions, functional connectivity investigates interactions between brain regions. In this study, we implemented and evaluated Probabilistic Independent Component Analysis (PICA) and generalized Canonical Correlation Analysis (gCCA) on resting state data of healthy subjects and subjects with ADHD disorders from NITRC database. This was done to detect brain functional connectivity and compare the results in normal and diseased subjects. In addition, speed of the methods was compared. Our study shows that relative to PICA, gCCA has higher precision and accuracy and lower computational complexity and run time in addition to capability of extracting more reproducible statistical maps in both control and ADHD subjects.

关键词： Correlation Magnetic resonance imaging Independent component analysis Educational institutions Biomedical engineering Probabilistic logic Basal ganglia

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Path planning of robotic fish based on genetic algorithm and modified dynamic programming

Path planning of robotic fish based on genetic algorithm and...

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International Conference on Advanced Mechatronic systems (ICAMechS)

作者： Qian Yang Mei Yu Shu Liu Zhong-ming Chai School of Control and Computer Engineering Electric Power University Beijing P. R. China Key Laboratory of Measurement and Control New Technology and System for Industrial Process North China Electric Power University Beijing P. R. China

In this paper, genetic algorithm and modified dynamic programming are applied to path planning of robotic fish for the first time. Using grid method to the environment modeling and applying genetic algorithm to the path planning, an optimal or sub-optimal robot path can be obtained. Since the robotic fish can't track linear motion, the robot path can be seen as several circular arc. Based on the optimal path obtained via genetic algorithm, modified dynamic programming algorithm is proposed to calculate the shortest circular arc path, fish velocity and direction in every step. Finally the experiment on the robotic fish control software shows the effectiveness of the proposed method.

关键词： Marine animals Robot kinematics Genetic algorithms Turning Path planning Dynamic programming

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Some Advanced Techniques in Reducing Time for Path Planning Based on Visibility Graph

Some Advanced Techniques in Reducing Time for Path Planning ...

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International Conference on Knowledge and systems Engineering (KSE)

作者： Tran Thi Nhu Nguyet Tran Van Hoai Nguyen Anh Thi Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Ho Chi Minh Vietnam Key Laboratory on Digital Control and System Engineering (DCSE) VNU-HCM Ho Chi Minh Vietnam

This paper describes some techniques based on polygon aggregation in reducing time for visibility graph in case of many obstacles. In path planning, the approaches are commonly used such as search-based, sampling-based or combinatorial planning. And visibility graph is one of the roadmaps of combinatorial planning. Building a visibility graph is a main phase in the whole process and theoretically it takes θ(nlogn). However, with some practical applications, for example one which has a large number of obstacles, this phase is very time-consuming. With the techniques proposed, the experiment result shows that the computing time gets a reduction factor of one-third approximately when the aggregation are used in preprocessing of building visibility graph.

关键词： Path planning Planning Clustering algorithms Complexity theory Educational institutions Robots Merging

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Research on consensus control for a class of high-order multi-agent systems

Research on consensus control for a class of high-order mult...

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作者： Zhang, Wenguang Guo, Zhenkai Beijing Key Laboratory of Measurement and Control New Technology and System for Industrial Process School of Control and Computer Engineering North China Electric Power University Beijing 102206 China School of Mathematics and Information Ludong University Yantai 264205 China

ISBN: (纸本)9789881725592

This paper researches the consensus problem of high-order multi-agent systems. A new dynamic neighbor-based protocol is proposed which contains two parts, one is the local feedback and the other is the distributed feedback of the first states of each agent. Sufficient conditions are derived for state consensus of the system. Finally, simulation results are shown the effectiveness of the obtained results. © 2011 Chinese Assoc of Automati.

关键词： Multi agent systems

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Generic Zernike-based surface representation of measured corneal surface data

Generic Zernike-based surface representation of measured cor...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Alexandros Soumelidis Zoltán Fazekas Margit Pap Ferenc Schipp System and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Applied Mathematics University of Pécs Pecs Hungary Department of Numerical Analysis Eötvös Lonránd University Budapest Hungary

Meshes of points over the unit disk were found some years ago that ensure the discrete orthogonality of the Zernike functions. These meshes are referred in the paper as generic Zernike meshes. Presently, however, the corneal surface points are measured, e.g., with reflection-based corneal topographers, and computed, with their respective built-in surface(-point) reconstruction programs, at other, that is, non-generic Zernike meshes. In the present paper, the corneal surface points measured over conventional non-generic Zernike meshes are converted - via cubic spline-interpolation and appropriate re-sampling - to surface points over generic Zernike meshes. With these spatial points as input points, discrete Zernike transformation is carried out. The resulting Zernike coefficients are then used to geometrically reconstruct the optically smooth corneal surface. In the work reported herein, generic Zernike meshes of different cardinalities were used and the resulting surface representations were evaluated. Then, the error-surfaces were compared to the ones resulting from the Zernike-based reconstructions of a cornea-like mathematical surface that had been properly fitted to the input data.

关键词： Surface reconstruction Polynomials Surface topography Cornea Chebyshev approximation Spline Humans

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Sport Video Classification Using an Ensemble Classifier

Sport Video Classification Using an Ensemble Classifier

引用

Iranian Machine Vision and Image Processing (MVIP)

作者： Mohamad Hoseyn Sigari Samaneh Abbasi Sureshjani Hamid Soltanian-Zadeh Control & Intelligent Processing Center of Excellence (CIPCE) School of Electrical & Computer Engineering College of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA

Sport video classification is an application of video analysis which can be useful in video indexing and retrieval. In this article, a new method for sport video classification using ensemble classifier is proposed. The proposed method uses 6 features: 3 dominant colors, dominant gray level, cut rate and motion rate. These features are classified by 4 simple classifiers in an ensemble classifier: Nearest Neighbor (NN), Linear Discriminant Analysis (LDA), Decision Tree (DT) and Probabilistic Neural Network (PNN). To combine the output of simple classifiers and make final decision, weighted majority vote is used while the weight of each simple classifier is equal to corresponding correct classification rate (CCR). Experimental result shows that the CCR of proposed system is 78.8%. In this experiment, 104 clips in 7 different sport classes are used: football, basketball, tennis, swimming, futsal, ski and box.

关键词： Feature extraction Color Image color analysis Classification algorithms Accuracy Artificial neural networks Histograms

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A novel type of trigonometric neural network trained by Extended Kalman Filter

A novel type of trigonometric neural network trained by Exte...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： M. Norouzi M. Mansouri M. Teshnehlab M. Aliyari Shoorehdeli Faculty of Engineering Department of Computer Engineering Science and Research Branch Islamic Azad University Iran Intelligent System Laboratory (ISLAB) Faculty of Electrical Engineering Control Department K.N. Toosi University of Technology Tehran Iran Faculty of Electrical Engineering Department of Mechatronics Engineering Advanced Process Automation &Control Laboratory (APAC) K.N. Toosi University of Technology Tehran Iran

In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison with conventional trigonometric neural networks and even other types of neural networks. Due to the low convergence rate and high posibility of trapping in a local minimum of backpropagation algorithm, Extended Kalman Filter algorithm is used to train the neural network's parameters which they appear in a nonlinear form. The Simulation of the suggested neural network based on the prediction of Mackey-Glass time series and identification of a nonlinear dynamic ystem reveals the efficiency of the proposed network. To show the efficiency of this method, the results are compared with the results of the others.

关键词： Biological neural networks Kalman filters Equations Neurons Vectors Covariance matrix Mathematical model

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