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2010 18th Iranian Conference on Electrical Engineering, ICEE 2010

作者： Afzali, Maryam Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9781424467600

Temporal lobe epilepsy (TLE) is a neurological disease that affects millions of individuals in the world. Majority of TLE patients suffer from refractory seizures. Determining abnormal/damaged regions of the brain that harbor seizure focus is a critical step towards treatment of TLE patients. Diffusion tensor imaging (DTI) is a non-invasive method that we use in this work to determine damaged regions of white matter in the brain. To this end, we apply two methods, voxel based morphometry (VBM) and fiber tracking. We use these methods along with two anisotropy maps (EAR and FA) extracted from the DTI data. We use DTI data of 31 subjects (12 normal subjects and 19 TLE patients) for testing and evaluation studies. The VBM method shows that TLE is associated with reduction of both of FA and EAR values in several regions within the temporal lobes. The tractography method shows abnormal diffusion characteristics in three fiber bundles (fornix, uncinate fasciculus, and cingulum). The results show that the EAR maps are less sensitive to noise than the FA maps and the EAR values change more than the FA values in TLE. ©2010 IEEE.

关键词： Diffusion tensor imaging

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An online predictor model as adaptive linear model and evolving Takagi-Sugeno model

An online predictor model as adaptive linear model and evolv...

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2010 International Symposium on Evolving intelligent Systems, EIS'10, Organised in the 2010 Annual Convention of the Society for Study of Artificial Intelligence and Simulation of Behaviour, AISB'10

作者： Kalhor, Ahmad Araabi, Babak N. Lucas, Caro Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran P.O. Box 14395/515 Tehran 14395 Iran Institute for Studies in Theoretical Physics and Mathematics School of Cognitive Sciences Tehran Iran

ISBN: (纸本)190295694X

In this paper, we suggest an online predictor model to follow the variations of a process with significant uncertainties. This model is defined as an adaptive linear model initially;however, it starts to evolve into a TS model and continues the process while the modeling error is higher than an adaptive threshold. The model habitually returns to an adaptive linear model when the modeling error becomes lower than the adaptive threshold. Evolving from a linear model to a nonlinear one and then returning to a linear model is performed through specially designed split and merge procedures. Finally, a real-world case study is conducted: prediction of monthly number of sunspots demonstrates the capabilities of the proposed approach.

关键词： Modal analysis

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Interactive visualization of hepatic parenchyma with applications to surgery simulators

Interactive visualization of hepatic parenchyma with applica...

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17th Iranian Conference in Biomedical Engineering, ICBME 2010

作者： Foruzan, Amir H. Chen, Yen-Wie Zoroofi, Reza A. Kaibori, Masaki College of Information Science and Engineering Ritsumeikan University Shiga Japan Control and Intelligent Processing Center of Excellence College of Engineering School of Electrical and Computer Engineering Tehran Iran Department of Surgery Hirakata Hospital Kansai Medical University Osaka Japan

ISBN: (纸本)9781424474844

Computer Assisted Diagnosis/Surgery systems provide an indisputable effect on the diagnosis and surgery of hepatic diseases. We developed a CAS system to prepare a virtual environment for a physician so as to interact with liver and decide on the therapy planning. The proposed system is composed of three modules, liver segmentation, vessel extraction, and visualization / interaction. It provides the physician a virtual scalpel to cut the liver. At first, inside of liver together with the vessels are shown to the physician and then the virtual surgery is started. A toggling option makes it easy to reveal inside of liver or make it opaque during the surgery. The width, height, and depth of the cut can be changed by the user. The proposed system is a framework which can later be extended to a complete CAD/CAS system for hepatic disease analysis and therapy planning. © 2010 IEEE.

关键词： Visualization

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Using PCA and LVQ neural network for automatic recognition of five types of white blood cells

Using PCA and LVQ neural network for automatic recognition o...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： P. R. Tabrizi S. H. Rezatofighi M. J. Yazdanpanah Control and Intelligent Processing Center of Excellence CIPCE school of Electrical and Computer Engineering University of Tehran Tehran Iran

Designing an effective classifier has been a challenging task in the previous methods proposed in the literature. In this paper, we apply a combination of feature selection algorithm and neural network classifier in order to recognize five types of white blood cells in the peripheral blood. For this purpose, first nucleus and cytoplasm are segmented using Gram-Schmidt method and snake algorithm, respectively; second, three kinds of features are extracted from the segmented areas. Then the best features are selected using Principal Component Analysis (PCA). Finally, five types of white blood cells are classified using Learning Vector Quantization (LVQ) neural network. The performance analysis of the proposed algorithm is validated by an expert's classification results. The efficiency of the proposed algorithm is highlighted by comparing our results with those reported in a recent article which proposed a method based on the combination of Sequential Forward Selection (SFS) as the feature selection algorithm and Support Vector Machines (SVM) as the classifier.

关键词： Classification algorithms Support vector machines Feature extraction Principal component analysis White blood cells Accuracy Artificial neural networks

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Real Data Testing of Model Parameter Estimation Methods for Macroscopic Traffic Flow Model

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IFAC Proceedings Volumes 2010年第16期43卷 419-424页

作者： Ehsan Jafari Behzad Moshiri Karim Salahshoor Amin Ramezani Control & Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran Department of Automation and Instrumentation Petroleum University of Technology Tehran Iran

In this paper a comparison for non-adaptive and adaptive traffic state estimators based on the nonlinear macroscopic traffic flow model is presented. In non-adaptive estimator, a Least Square based method was used to estimate model parameters with off-line data. Beside this non-adaptive estimator, three adaptive estimators were designed and tested. In these adaptive estimators, online estimation of the model parameters were done based on Least Square, joint filtering and dual filtering methods. In all mentioned estimators, extended Kalman filtering method was used to estimate traffic variables. Finally, Real data testing results of these estimators for Interstate 494 in metro freeway, Minnesota, USA are presented.

关键词： Traffic state estimation Stochastic macroscopic traffic flow model Extended Kalman filter On-line model parameter estimation Least Square

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Multi-scale approach for retinal vessel segmentation using medialness function

Multi-scale approach for retinal vessel segmentation using m...

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IEEE International Symposium on Biomedical Imaging

作者： Elahe Moghimirad Seyed Hamid Rezatofighi Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering Faculty of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424441259;9781424441266

Automated segmentation of retinal vessels in optic fundus images has been the most prevailing effort in many researches during recent years. In this paper, we propose a multi-scale method based on a weighted 2D medialness function. The result of the medialness function is first multiplied by the eigenvalues of the Hessian matrix in every pixel of the image in order to extract vessel's medial-lines. Next, by extracting the centerlines of vessels and estimation of radius of vessels, the retinal vessels are segmented. Finally, the performance of our proposed method is evaluated by the DRIVE and STARE databases and compared with those of several recent methods.

关键词： Retinal vessels Image segmentation Eigenvalues and eigenfunctions Retina Filters Image databases Blood vessels Biomedical imaging Vectors Pathology

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Alleviating the Cold-Start Problem of Recommender Systems Using a New Hybrid Approach

Alleviating the Cold-Start Problem of Recommender Systems Us...

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International Symposium on Telecommunications

作者： Javad Basiri Azadeh Shakery Behzad Moshiri Morteza Zi Hayat School of Electrical and Computer Engineering University of Tehran Control and Intelligent Processing Center of Excellence School of ECE University of Tehran

ISBN: (纸本)9781424481835

Recommender systems have become significant tools in electronic commerce, proposing effectively those items that best meet the preferences of users. A variety of techniques have been proposed for the recommender systems such as, collaborative filtering and content-based filtering. This study proposes a new hybrid recommender system that focuses on improving the performance under the "new user cold-start" condition where existence of users with no ratings or with only a small number of ratings is probable. In this method, the optimistic exponential type of ordered weighted averaging (OWA) operator is applied to fuse the output of five recommender system strategies. Experiments using MovieLens dataset show the superiority of the proposed hybrid approach in the cold-start conditions.

关键词： Recommender system Collaborative filtering Content-based filtering Demographic- information Hybrid approach OWA

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A chaotic model for generating heart rate variability signal using integral pulse frequency modulation

A chaotic model for generating heart rate variability signal...

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作者： Lak, Mahdi Dabanloo, Nader Jafarnia Setarehdan, S. Kamaledin Biomedical Engineering Faculty Science and Research Branch Islamic Azad University P.O. Box: 4515/775 Tehran Iran Control and Intelligent Processing Center of Excellence Faculty of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424473182

Heart rate variability (HRV) is a very useful signal to investigate the activity of the autonomic nervous system (ANS), which affects and the heart function. Constructing a mathematical model for producing artificial HRV signal is needed to get a conceptual understanding of how ANS controls the heart rate (HR). The integral pulse frequency modulation (IPFM) structure is employed in this paper to model the sino-atrial node (SAN). Considering the complexity and nonlinear dynamics in the real HRV signal, a chaotic input is used in the proposed model. Instead of using a fixed threshold in IPFM model as in most previous works, we applied an appropriate variable signal, which has nonlinear chaotic dynamics. After running the model, the power spectrum of the output signal is extracted, which was then followed by calculating the nonlinear characteristics. The results were closely correlated with the real data, which confirm the effectiveness of the proposed model.

关键词： Frequency modulation

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Risk assessment of coronary arteries heart disease based on neuro-fuzzy classifiers

Risk assessment of coronary arteries heart disease based on ...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Mohammad Danesh Zand Amir Hossein Ansari Caro Lucas Reza Aghaee Zade Zoroofi Department of Electrical & Computer Engineering University of Tehran Tehran Iran Control & Intelligent Processing Center of Excellence University of Tehran Tehran Iran

Coronary artery heart disease is one of the main reasons of death in under development countries such as Iran. Based on vagueness in data and uncertainty in decision making finding an optimal way for diagnosis would be helpful. The main goal of this article is to change the linguistic terms which doctors use for representing coronary heart disease possibility into classified stages. Indeed the medical diagnosis can be used as an issue of pattern recognition by an input vector of features introduced to a system so the corresponding risk of a particular disease can be estimated with this system. In this paper we used an adaptive network-based inference system in order to assess the risk of coronary artery heart diseases .With this point of view that fault in medical diagnosis are more errors of omission than of commission, we are going to reduce this diagnosis defect with Neuro-fuzzy networks such as Multi-Layer Perceptron (MLP) and an inference Neuro-fuzzy network such as ANFIS. In the last section we will compare these methods to show that ANFIS can obtain the best accommodation with doctor's opinions.

关键词： Diseases Heart Hardware design languages

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A Hybrid Approach to Predict Churn

A Hybrid Approach to Predict Churn

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IEEE Asia-Pacific Conference on Services Computing (APSCC)

作者： Javad Basiri Fattaneh Taghiyareh Behzad Moshiri School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran

Acquiring new customers in any business is much more expensive than trying to keep the existing ones. As a result, many prediction algorithms have been proposed to detect churning customers. In this paper, the ordered weighted averaging (OWA) technique is brought to the attention of marketing researchers. We have applied OWA technique to improve the prediction accuracy of existing churn management systems. The decision lists of underlying prediction algorithms have been fused using OWA algorithm. Applied to the database of a telecommunication company, this method is found to significantly improve accuracy in predicting churn compared to the best existing result in the literature of the churn management. Our findings lead us to believe that using OWA technique could cause to increase profit for the companies.

关键词： Classification algorithms Prediction algorithms Open wireless architecture Bagging Boosting Artificial neural networks Classification tree analysis

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