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Color doppler echocardiographic image analysis via shape and texture features

Color doppler echocardiographic image analysis via shape and...

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International Conference on Bioinformatics and Biomedical Technology (ICBBT)

作者： S. Nandagopalan C. Dhanalakshmi B. S. Adiga N. Deepak Department of Computer Science & Engineering Bangalore Institute of Technology Bangalore India Parallel Computing Division Tata Consultancy Services Limited Bangalore India Department of Echocardiography Sciences and Research Sri Jayadeva Institute of Cardiovascular Bangalore India Network Division Eshamount Technologies Bangalore India

ISBN: (纸本)9781424467754;9781424467761

Doppler imaging allows evaluation of blood flow patterns, direction, and velocity. The color (red, blue, and mosaic) signify the direction of the blood flow. By analyzing this color Doppler, it is possible to detect heart diseases like mitral and aortic stenosis, mitral, tricuspid, and aortic regurgitation, and Left Ventricle (LV) hypertrophy. We present 3 methods to extract low level features namely color histogram mean, standard deviation, skewness, kurtosis, and texture features such as energy, entropy, contrast, homogeneity of the region of interest (ROI) in a color Doppler echocardiographic image. The first method is based on conventional K-Means algorithm to segment the image. A modified fast K-Means implemented using SQL is the second method presented in this paper. Finally, segmentation is achieved through pixel classification approach which is found being the most efficient. The proposed technique decomposes the image into foreground pixels representing color information and background pixels which are grayscale. Thus, we apply morphological operations, Gaussian blur, and threshold to obtain a distinct object for quantitative measurements. Without doing any modifications to the foreground pixels, we compute histogram statistics of the shape and texture features. Hence, with our proposed method both qualitative and quantitative analysis can be done. Our technique is applied on variety of color Doppler patient images and the results show that it is computationally efficient and abnormality detection is satisfactory.

关键词： Image color analysis Image texture analysis Shape Blood flow Histograms Image segmentation Pixel Cardiac disease Feature extraction Entropy

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Improved prostate cancer localization with spatially regularized dynamic contrast-enhanced magnetic resonance imaging

Improved prostate cancer localization with spatially regular...

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IEEE International Symposium on Biomedical Imaging

作者： Liu Lukai Masoom A. Haider Deanna L. Langer Imam Samil Yetik Medical Imaging Research Center (MIRC) Electrical & Computer Engineering Department Illinois Institute of Technology Chicago IL USA Joint Department of Medical Imaging Mount Sinai Hospital University Health Network Toronto Canada Institute of Medical Science University of Toronto Toronto Canada

ISBN: (纸本)9781424441259;9781424441266

Imaging methods to localize prostate cancer with sufficient accuracy are extremely useful in guiding biopsy, radiotherapy and surgery as well as to monitor disease progression. Imaging prostate cancer with multispectral magnetic resonance imaging (MRI) has shown a superior performance when compared to classical imaging modality transrectal ultrasound (TRUS). An important component of multispectral MRI is dynamic contrast-enhanced magnetic resonance imaging (DCE MRI). However, parametric images based on DCE MRI suffer from low signal-to-noise ratio (SNR). In this study, we propose a kinetic parametric imaging method with DCE MRI to overcome this problem using spatial regularization for improved prostate cancer localization. We demonstrate that the proposed method outperforms pixel-wise parametric imaging method, and that the performance of resulting tumor localization has a considerable improvement. Both visual and quantitative evaluations based on a task-based approach focused on tumor localization are provided.

关键词： Prostate cancer Magnetic resonance imaging Ultrasonic imaging Neoplasms Biopsy Oncological surgery Monitoring Diseases Signal to noise ratio Kinetic theory

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Automatic Segmentation and Ventricular Border Detection of 2D Echocardiographic Images Combining K-Means Clustering and Active Contour Model

Automatic Segmentation and Ventricular Border Detection of 2...

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International Conference on computer and network Technology (ICCNT)

作者： S. Nandagopalan B.S. Adiga C. Dhanalakshmi N. Deepak Department of Computer Science & Engineering Bangalore Institute of Technology Bangalore India Parallel Computing Division TATA Consultancy Services Limited Bangalore India Department of Echocardiography Sri Jayadeva Institute of Cardiovascular Sciences and Research Bangalore India Network Division Eshamount Technologies Bangalore India

Accurate analysis of 2D echocardiographic images is vital for diagnosis and treatment of heart related diseases. For this task, extraction of cardiac borders must be carried out. In particular, automatic quantitative measurements of Left Ventricle (LV), Right Ventricle (RV), Left Atrium (LA), Right Atrium, Valve size, etc. are essential. We believe that automatic processing of these echo images could speed up the clinical decisions and reduce human error. In this paper we focus on automatic segmentation of echocardiographic images of different views (Long Axis View, Short Axis View, Apical 4-chamber View) to extract ventricle and atrium borders for detecting heart abnormalities. A novel approach of combining the K-Means clustering algorithm for segmentation and active contour model for boundary detection is proposed. Since conventional K-Means implementation is not time efficient, we propose a novel algorithm called fast K-Means SQL based on (i) TRUNCATE-INSERT instead of DELETE-INSERT for table updates (ii) denormalized database design and tuning (iii) minimal table joins, to accelerate the image segmentation. Thus, with this approach an image of resolution 400 × 250 takes just 16 seconds, whereas the conventional method takes 950 seconds. After the operator selects the initial contour in the appropriate part of the echocardiographic image, the deformable contour (snake) converges to the boundaries of the region of interest (ROI). Once the shape of the ventricle or atrium is extracted, we apply coordinate geometry to compute all the necessary parameters required for clinical decision. Normally, ultrasound images are embedded with speckle noise; hence we first apply median filter and then the image segmentation. Experiments are conducted using relatively large set of images obtained from a cardiology hospital. The results show that our proposed method is computationally efficient and 2D measurements are accurate.

关键词： Image segmentation Active contours Heart Clustering algorithms Image analysis Cardiac disease Cardiovascular diseases Particle measurements Size measurement Valves

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A fast K-Means algorithm for the segmentation of echocardiographic images using DBMS-SQL

A fast K-Means algorithm for the segmentation of echocardiog...

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International Conference on computer and Automation engineering, ICCAE

作者： S. Nandagopalan C. Dhanalakshmi B. S. Adiga N. Deepak Department of Computer Science & Engineering Bangalore Institute of Technology Bangalore India Parallel Computing Division Tata Consultancy Services Limited Bangalore India Department of Echocardiography Sciences and Research Bangalore Sri Jayadeva Institute of Cardiovascular India Network Division Eshamount Technologies Bangalore India

ISBN: (纸本)9781424455690

An efficient K-Means clustering algorithm is proposed using the power of SQL in a relational Database Management environment. Further, this method is applied to segment 2D echocardiography images. We propose this method mainly to improve the speed of segmentation process for further clinical analysis and diagnosis (example: Left Ventricular (LV) boundary detection and other 2D quantitative measurements) of a patient. With few initial image processing steps like median filtering, etc, our proposed K-Means SQL algorithm is applied on the image to identify the segments. Since segmentation alone cannot resolve the anatomical ambiguities present in echocardiogram images, few post segmentation steps like median filtering, Canny edge detection operator, Gaussian sharpening, and morphological operations are applied to obtain venrtricle borders. We identify steps that would normally take more time in conventional K-means algorithm and provide appropriate alternatives in SQL. We compare the conventional K-means algorithm with K-Means SQL algorithm for a set of sample echocardiogram images and the experiments show that our method is superior in terms of quality of segmentation, running time, and scalability.

关键词： Image segmentation Clustering algorithms Filtering Relational databases Energy management Environmental management Echocardiography Clinical diagnosis Velocity measurement Image processing

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A hybrid discrete PSO-SA algorithm to find optimal elimination orderings for Bayesian networks

A hybrid discrete PSO-SA algorithm to find optimal eliminati...

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International Conference on Industrial and Information Systems, IIS

作者： Xuchu Dong Dantong Ouyang Dianbo Cai Yonggang Zhang Yuxin Ye Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre China Telecom Corporation Limited Changchun Jilin China

In this paper, a hybrid algorithm named DPSOSA is proposed to find near-to-optimal elimination orderings in Bayesian networks. DPSO-SA is a discrete particle swarm optimization method enhanced by simulated annealing. ... 详细信息

关键词： Computational modeling Adaptation model

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Cooperative coevolutionary genetic algorithms to find optimal elimination orderings for Bayesian networks

Cooperative coevolutionary genetic algorithms to find optima...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Xuchu Dong HaiHong Yu Dantong Ouyang Dianbo Cai Yuxin Ye Yonggang Zhang Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre China Telecom Corporation Limited Changchun Jilin China

According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are proposed. Based on these works, six cooperative coevolutionary genetic algorithms are constructed. Numerical experiments show that these algorithms are more robust than other existing swarm intelligence methods when solving the elimination ordering problem.

关键词： Genetics Bayesian methods Robustness

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Widely tunable multiband reconfigurable patch antenna for wireless applications

Widely tunable multiband reconfigurable patch antenna for wi...

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European Conference on Antennas and Propagation, EuCAP

作者： H. F. AbuTarboush R. Nilavalan K M. Nasr H. S. Al-Raweshidy D. Budimir Wireless Network & Communication Centre School of Engineering & Design Brunei University West London UK Wireless Communication Technologies National Physical Laboratory Teddington UK Wireless Communications Research Group Department of Electronics & Computer Science Westminster University UK

A design of a low profile reconfigurable microstrip patch antenna is presented. The antenna consists of four sup-patches connected to one feed line, each sub-patch generates a single band. By placing a variable capacitor at the input of the sub-patches, the impedance matching frequency of the antenna can be tuned over a wide range starting from 0.92 GHz to 2.98 GHz with total tunability rang of 2060 MHz. The proposed antenna designed to operate in the Global System for Mobile communication (GSM900, 880-960 MHz)/ Digital Communication System (DCS1800, 1710-1880 MHz)/ Universal Mobile Telecommunication System (UMTS, 1920-2170 MHz)/ Wireless Local Area network (WLAN, 2400-2483.5 MHz)/ and Worldwide Interoperability for Microwave Access (WiMAX, 2495-2700 MHz). The total size of the proposed antenna is 50 × 50 mm 2 which is suitable for small wireless devices.

关键词： Patch antennas Wireless LAN Microstrip antennas Antenna feeds Capacitors Impedance matching Frequency Microwave antennas Mobile antennas GSM

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An adaptive multi-heuristic ant colony system for finding optimal elimination orderings in Bayesian networks

An adaptive multi-heuristic ant colony system for finding op...

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International Conference on Electrical engineering, Computing Science and Automatic Control (CCE)

作者： Xuchu Dong Yonggang Zhang Dianbo Cai Haihong Yu Yuxin Ye Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre China Telecom Corporation Limited Changchun Jilin China

To find an optimal elimination ordering for Bayesian networks, a multi-heuristic-based ant colony system named MHC-HS-ACS is proposed. MHC-HS-ACS uses a set of heuristics to guide the ants to search solutions. The heuristic set can evolve with the searching procedure in an adaptive way. MHC-HS-ACS also utilizes a heuristic-based local search to accelerate its convergence. Computational experiments show that MHC-HS-ACS can find very high quality solutions.

关键词： Bayesian methods Ethics Junctions Conferences Electrical engineering IEEE catalog Inference algorithms

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Comparison of hybrid feature selection models on gene expression data

Comparison of hybrid feature selection models on gene expres...

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International Conference on ICT and Knowledge engineering

作者： Patharawut Saengsiri Phayung Meesad Sageemas Na Wichian Unger Herwig Department of Information Technology Faculty of Information Technology KMUTNB Bangkok Thailand Department of Applied Science and Social College of Industrial Technology KMUTNB Bangkok Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education KMUTNB Bangkok Thailand Department of Communication Network Faculty of Mathematics and Computer Science Fern University of Hagen Germany

Microarray data contains thousands of genes which are used to evaluate expression level. However, most of them are not associated with cancer diseases and leads to the curse of dimensionality. The challenge based on microarray data is feature selection which searches for subsets of informative genes. At the moment, these techniques focus on filter and wrapper approaches to discover subsets of genes. Filter approach is better than wrapper approach in terms of time consuming. On the contrary, the accuracy of wrapper approach is higher than that of filter approach. However, it is more beneficial to reduce the time process and increase accuracy simultaneously when searching for subsets of genes. Thus, this paper proposes comparison of hybrid feature selection models on gene expression datasets, this consists of four steps 1) filter subgroup of gene using Correlation based Feature Selection (CFS), Gain Ratio (GR), and Information Gain (INFO) 2) transfers output of each filter method into a wrapper approach that's based on the Support Vector Machine (SVM) classifier and two heuristic searches which are Greedy Search (GS) and Genetic Algorithm (GA) 3) generate hybrid feature selection model CFSSVMGA, CSFSVMGS, GRSVMGA, GRSVMGS, INFOSVMGA, and INFOSVMGS 4) performance comparison using precision, recall, F-measure, and accuracy rate. Results from the experiment concluded the CFSSVMGA model outperformed other models on three public gene expression datasets.

关键词： Gene expression Accuracy Classification algorithms Cancer Support vector machines Filtering algorithms Colon

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Online information sharing issues in website personalization

Online information sharing issues in website personalization

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International Conference on User Science and engineering (i-USEr)

作者： Mohd Norhisham Razali Fariza Hanis Abdul Razak Tan Soo Fun Rozita Hanapi Software Engineering School of Engineering and Information Technology Universiti Malaysia Sabah Malaysia Network and System Management Software Engineering and Information Technology Universiti Malaysia Sabah Malaysia Department of System Science Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor Darul Ehsan Malaysia Office System Management Faculty of Office Management and Technology Universiti Teknologi MARA Shah Alam Selangor Darul Ehsan Malaysia

Website Personalization is one of strategic technique in delivering services in online applications. A part of process for building personalization applications is to collect particular information from the user which involves information sharing. However, the awareness about privacy concerns and security threats have caused to non-sharing behavior among the Internet Users. This situation have caused website personalization cannot be built to serve its purposes. This paper aims to investigate the people's behavior and to study the propensity of information sharing attitude in two different environments and cultures. The two environments are between real-life and online while the two cultures are between Malaysian and non-Malaysian. Since this is an exploratory study, interview with five (5) persons have been conducted. The qualitative technique that chooses was recommended for any exploratory study. The findings of this study explained the understanding of behaviors and the factors of Information Sharing. The factors are the cultural factors, the platform of sharing and the behavior of information sharing in web personalization. The sharing behavior in two environments and cultures were also compared. The data collected from the interviews have generalizing the speculations and issues in information sharing which have been discussed at the end section of this paper.

关键词： Privacy Internet Interviews Cultural differences Business Context Security

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