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IEEE International Symposium on Biomedical Imaging

作者： Amal Farag Asem Ali James Graham Aly Farag Salwa Elshazly Robert Falk Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Medical Imaging Division Jewish Hospital Louisville KY USA

This paper examines the effectiveness of geometric feature descriptors, common in computer vision, for false positive reduction and for classification of lung nodules in low dose CT (LDCT) scans. A data-driven lung nodule modeling approach creates templates for common nodule types, using active appearance models (AAM); which are then used to detect candidate nodules based on optimum similarity measured by the normalized cross-correlation (NCC). Geometric feature descriptors (e.g., SIFT, LBP and SURF) are applied to the output of the detection step, in order to extract features from the nodule candidates, for further enhancement of output and possible reduction of false positives. Results on the clinical ELCAP database showed that the descriptors provide 2% enhancements in the specificity of the detected nodule above the NCC results when used in a k-NN classifier. Thus quantitative measures of enhancements of the performance of CAD models based on LDCT are now possible and are entirely model-based. Most importantly, our approach is applicable for classification of nodules into categories and pathologies.

关键词： Feature extraction Lungs Training Databases Solid modeling Principal component analysis Computed tomography

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Creation of virtual worlds from 3D models retrieved from content aware networks based on sketch and image queries

Creation of virtual worlds from 3D models retrieved from con...

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12th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2011

作者： Semertzidis, Theodoros McGuinness, Kevin Daras, Petros Makris, Lambros E'Connor, Noel O. Strintzis, Michael G. Information Processing Laboratory Department of Electrical and Computer Engineering Aristotle University of Thessaloniki GR54124 Thessaloniki Greece Informatics and Telematics Institute Centre for Research and Technology Hellas GR57001 Thessaloniki Greece CLARITY: Center for Sensor Web Technology Dublin City University Glasnevin Dublin 9 Ireland

The recent emergence of user generated content requires new content creation tools that will be both easy to learn and easy to use. These new tools should enable the user to construct new high-quality content with minimum effort;it is essential to allow existing multimedia content to be reused as building blocks when creating new content. In this work we present a new tool for automatically constructing virtual worlds with minimum user intervention. Users can create these worlds by drawing a simple sketch, or by using interactively segmented 2D objects from larger images. The system receives as a query the sketch or the segmented image, and uses it to find similar 3D models that are stored in a Content Centric Network. The user selects a suitable model from the retrieved models, and the system uses it to automatically construct a virtual 3D world.

关键词： Virtual reality

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Towards energy saving and load balancing data aggregation for wireless sensor networks

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Information Technology Journal 2011年第2期10卷 409-415页

作者： Liang, Wei Xu, Jianbo Liu, Yuanyuan Key Laboratory of Knowledge Processing and Networked Manufacturing School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan 411201 China Department of Electrical Engineering Guangdong Songshan Polytechnic College Shaoguang 512126 China

In this study, we focus on the development of energy efficient and achievable load balancing mechanisms for wireless sensor networks. Due to resource constraint and tremendous amount of sensors, one possible way of achieving maximum lifetime of the network is applying data aggregation on sensor data. However, existing approaches introduce significant computation and control overheads that often not suitable for sensor networks applications. In view of this, we propose an in-network data aggregation scheme by exploiting the inherent spatial correlation of the sensed data. Each sensor multiplies its reading with a random coefficient and sends the product to the next hop to calculate a weighted sum of all the massage. Instead of receiving individual sensor readings, the sink will receive all weighted sum and restore the original data. By doing so, each node only performs one addition and one multiplication in order to compute one weighted sum and consume the same amount of energy. Simulation results demonstrate that the proposed scheme is efficient and outperforms existing schemes in terms of energy gain and network lifetime. © 2011 Asian Network for Scientific Information.

关键词： Energy efficiency

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Dynamic anti-windup design in anticipation of actuator saturation

Dynamic anti-windup design in anticipation of actuator satur...

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作者： Wu, Xiongjun Lin, Zongli Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 United States

ISBN: (纸本)9781457700804

In a traditional anti-windup design, the anti-windup mechanism is set to be activated as soon as the control signal saturates the actuator. A recent innovation of delaying the activation of the anti-windup mechanism, both static and dynamic, until the saturation reaches to a certain level of severity has led to a performance improvement of the resulting closed-loop system. More recently, it has been shown that significant further performance improvements can be obtained by activating a static anti-windup mechanism in anticipation of actuator saturation, in comparison with the delayed activation design. This paper demonstrates that anticipatory activation of a dynamic anti-windup mechanism would also lead to significant performance improvements over both the immediate and delayed activation schemes. © 2011 AACC American Automatic Control Council.

关键词： Chemical activation

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Effect of Different Diffusion Maps on Registration Results

Effect of Different Diffusion Maps on Registration Results

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Iranian Machine Vision and Image processing (MVIP)

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory (BiSIPL) Sharif University of Technology Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper, we compare registration results obtained using different diffusion maps extracted from diffusion tensor imaging (DTI). Fractional Anisotropy (FA) and Ellipsoidal Area Ratio (EAR) are two diffusion maps (indices) that may be used for image registration. First, we use FA maps to find deformation matrix and register diffusion weighted images. Then, we use EAR maps and finally we use both of FA and EAR maps to register diffusion weighted images. The difference between FA values before deformation and after registration using the FA alone or EAR alone has a median of 0.57 and using both of them has a median of 0.29. Therefore, the results of registration using both of the FA and EAR indices are superior to those obtained using only one of them alone.

关键词： Ear Diffusion tensor imaging Tensile stress Registers Eigenvalues and eigenfunctions Anisotropic magnetoresistance Image registration

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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2011 18th Iranian Conference of Biomedical engineering, ICBME 2011

作者： Sabahi, Hadi Soltanian-Zadeh, Hamid Scarpace, Lisa Mikkelsen, Tom 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 Hospital Detroit MI 48202 United States Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9781467310055

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures. © 2011 IEEE.

关键词： Tumors

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The texture classification using the fusion of decisions from different texture classifiers

The texture classification using the fusion of decisions fro...

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International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： S. Pharsook T. Kasetkasem P. Larmsrichan S. Siddhichai T. Chanwimaluang T. Isshiki Department of Electrical Engineering Kasetsart University Thailand Image Processing Laboratory National Electronics and Computer Technology Center Thailand Department of Communication and Integrated Systems Tokyo Institue of Technology Japan

The improved of texture classification accuracy by using the probability weighted combination method of three texture features extraction consist of thE0020 Gray-Level Co-occurrence Matrix (GLCM), Semivariogram Function and Gaussian Markov Random Fields (GMRFs). Five different textures images are used in the experiment. The classifier that use for classify the extracted features in this research is Support Vector Machines (SVMs). The experimental result shows that the average accuracy of the combination method with probability weight up to 95.71%, which is better than the simple combination method about 2%.

关键词： Markov processes Tutorials Entropy Arrays Sensors

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Integrated database system for mobile dietary assessment and analysis

Integrated database system for mobile dietary assessment and...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Marc Bosch TusaRebecca Schap Fengqing Zhu Nitin Khanna Carol J. Boushey Edward J. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Foods and Nutrition Purdue University West Lafayette IN USA

Of the 10 leading causes of death in the US, 6 are related to diet. Unfortunately, methods for real-time assessment and proactive health management of diet do not currently exist. There are only minimally successful tools for historical analysis of diet and food consumption available. In this paper, we present an integrated database system that provides a unique perspective on how dietary assessment can be accomplished. We have designed three interconnected databases: an image database that contains data generated by food images, an experiments database that contains data related to nutritional studies and results from the image analysis, and finally an enhanced version of a nutritional database by including both nutritional and visual descriptions of each food. We believe that these databases provide tools to the healthcare community and can be used for data mining to extract diet patterns of individuals and/or entire social groups.

关键词： Image analysis Image databases Visualization Servers Visual databases

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Robust ℋ∞ output feedback control of discrete-time networked systems with adaptive quantizers

Robust ℋ∞ output feedback control of discrete-time network...

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IEEE Conference on Decision and Control

作者： Faiz Rasool Dan Huang Sing Kiong Nguang Department of Electrical and Computer Engineering University of Auckland Auckland New Zealand Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiaotong University Shanghai China

Quantization effects are inevitable in networked control systems (NCSs). These quantization effects can be reduced by increasing the number of quantization levels. However, increasing the number of quantization levels may lead to network congestion, (i.e., the network needs to transfer more information than its capacity). In this paper, we investigate the problem of designing a robust ℋ ∞ output feedback controller for discrete-time networked systems with an adaptive quantization density or limited information. More precisely, the quantization density is designed to be a function of the network load condition which is modeled by a Markov process. A stability criterion is developed by using Lyapunov-Krasovskii functional and sufficient conditions for the existence of a dynamic quantized output feedback controller are given in terms of Bilinear Matrix Inequalities(BMIs). An iterative algorithm is suggested to obtain quasi-convex Linear Matrix Inequalities (LMIs) from BMIs. An example is presented to illustrate the effectiveness of the proposed design.

关键词： Quantization Delay Linear matrix inequalities Markov processes Closed loop systems Stability analysis Output feedback

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Robust partially mode delay-dependent ℋ∞ output feedback control of discrete-time networked control systems

Robust partially mode delay-dependent ℋ∞ output feedback c...

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American Control Conference (ACC)

作者： Seunghwan Chae Dan Huang Sing Kiong Nguang The Department of Electrical and Computer Engineering University of Auckland Auckland New Zealand Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiaotong University Shanghai China

This paper examines robust partially mode de lay dependent H ∞ output feedback controller design for discrete-time systems with random communication delays. A finite state Markov chain with partially known transition probabilities is used to model random communication delays between sensors and controller. Based on Lyapunov-Krasovskii functional, a novel methodology for designing a partially mode delay-dependent output feedback controller is proposed. Using cone complementarity linearization algorithm bilinear matrix inequalities (BMIs) are solved to obtain the controller gains. We also show that the results for completely known transition probabilities and completely unknown transition probabilities can be derived as special cases of our result. The effectiveness of the proposed design methodology is demonstrated by a numer ical example. To the best of authors' knowledge, the problem of designing an output feedback controller for a partially known transition probability has not been fully investigated.

关键词： Delay Markov processes Output feedback Linear matrix inequalities Robustness Silicon

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