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2012 International Conference on Computer Science and Information processing, CSIP 2012

ISBN: (纸本)9781467314114

The proceedings contain 361 papers. The topics discussed include: cross-strait information integration application strategy planning-a case study of Kinmen-Xiamen;the observability analysis of aerial moving target location based on dual-satellite geolocation system;application of digital image processing in the measurement of casting surface roughness;study of wavelet denoising in images of vacuum switching arc;research on trust mechanism in military information grid;a new algorithm for packing unequal disks in a larger circle;new tool radius compensation algorithm and implementation;parallel decoupling algorithm for solving the block tri-diagonal linear equations;methods analysis of the liquid ion-exchanged to manufacture the optical waveguide on the glass based;experimental study on quantum data stream cipher using homodyne detection;and the optimal model reduction method for spatially distributed system based on simulated annealing algorithm.

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Exploiting parallelism in a X-ray Tomography Reconstruction Algorithm on Hybrid Multi-GPU and Multi-core Platforms

Exploiting Parallelism in a X-ray Tomography Reconstruction ...

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International Symposium on parallel and distributed processing with Applications, ISPA

作者： Ernesto Liria Daniel Higuero Monica Abella Claudia de Molina Manuel Desco Universidad Carlos III de Madrid Madrid Spain Hospital General Universitario Gregorio Marañón Madrid Spain

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. Currently there are a strong need to speed-up the reconstruction of XRay CT data in order to extend its clinical applications. We present an efficient modular implementation of an FDK-based reconstruction algorithm that takes advantage of the parallel computing capabilities and the efficient bilinear interpolation provided by general purpose graphic processing units (GPGPU). The proposed implementation of the algorithm is evaluated for a high-resolution micro-CT and achieves a speed-up of 46, while preserving the reconstructed image quality.

关键词： Graphics processing unit Computed tomography image reconstruction parallel processing X-ray imaging Geometry Detectors

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Evaluation and comparison of cell nuclei detection algorithms

Evaluation and comparison of cell nuclei detection algorithm...

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IEEE 16th International Conference on Intelligent Engineering Systems, INES 2012

作者： Szénási, Sándor Vámossy, Zoltán Kozlovszky, Miklós Óbuda University Doctoral School of Applied Informatics Budapest Hungary Óbuda University John Von Neumann Faculty of Informatics Budapest Hungary MTA SZTAKI Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9781467326957

The processing of microscopic tissue images and especially the detection of cell nuclei is nowadays done more and more using digital imagery and special immunodiagnostic software products. Since several methods (and applications) were developed for the same purpose, it is important to have a measuring number to determine which one is more efficient than the others. The purpose of the article is to develop a generally usable measurement number that is based on the "gold standard" tests used in the field of medicine and that can be used to perform an evaluation using any of image segmentation algorithms. Since interpreting the results themselves can be a pretty time consuming task, the article also contains a recommendation for the efficient implementation and a simple example to compare three algorithms used for cell nuclei detection. © 2012 IEEE.

关键词： image segmentation

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The Web-Based Assessment for Inundated Area Detection

The Web-Based Assessment for Inundated Area Detection

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Ponthip Limlahapun Hiromichi Fukui Keio Research Institute Keio University Kanagawa Japan Chubu Institute for Advanced Studies Professor Director of International Digital Earth Applied Science Research Center (IDEAS) Chubu University Aichi Japan

An object-based image processing technique is applied to detect inundated areas using Land sat images. An interoperable Web-based system was developed to conduct the analyses so that redundant steps in Land sat image processing can be effectively eliminated. A review process is used to discover and develop suitable algorithms to automatically detect inundated areas and immediately transfer the results to the Web-based interface. This is a significant improvement over currently available methods for inundation detection systems. The tool is expected to be a practical inundated area detection function and be applicable across wide-reaching areas.

关键词： Satellites Feature extraction image segmentation Remote sensing MATLAB Earth

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Statistical Parametric Models and Inference for Biomedical Signal processing: Applications in Speech and Magnetic Resonance Imaging

Statistical Parametric Models and Inference for Biomedical S...

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作者： Hong, Jung Ook Harvard University

学位级别：Ph.D.

In this thesis, we develop statistical methods for extracting significant information from biomedical signals. Biomedical signals are not only generated from a complex system but also affected by various random factors during their measurement. The biomedical signals may then be studied in two aspects: observational noise that biomedical signals experience and intrinsic nature that noise-free signals possess. We study Magnetic Resonance (MR) images and speech signals as applications in the one- and two-dimensional signal representation. In MR imaging, we study how observational noise can be effectively modeled and then removed. Magnitude MR images suffer from Rician-distributed signal-dependent noise. Observing that the squared-magnitude MR image follows a scaled non-central Chi-square distribution on two degrees of freedom, we optimize the parameters involved in the proposed Rician-adapted Non-local Mean (RNLM) estimator by minimizing the Chi-square unbiased risk estimate in the minimum mean square error sense. A linear expansion of RNLM's is considered in order to achieve the global optimality of the parameters without data-dependency. parallel computations and convolution operations are considered as acceleration techniques. Experiments show the proposed method favorably compares with benchmark denoising algorithms. Parametric modelings of noise-free signals are studied for robust speech applications. The voiced speech signals are often modeled as the harmonic model with the fundamental frequency, commonly assumed to be a smooth function of time. As an important feature in various speech applications, pitch, the perceived tone, is obtained by way of estimating the fundamental frequency. In this thesis, two model-based pitch estimation schemes are introduced. In the first, an iterative Auto Regressive Moving Average technique estimates harmonically tied sinusoidal components in noisy speech signals. Dynamic programming implements the smoothness of the fundamental

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A Novel Approach for Regularized Signal Deconvolution Based on Hybrid Swarm Intelligence: Application to Neutron Radiography

A Novel Approach for Regularized Signal Deconvolution Based ...

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Slami Saadi Abderrezak Guessoum Maamar Bettayeb Department of Electronics University Ziane Achour Djelfa Algeria Department of Electronics LATSI Laboratory University Saad Dahlab Burgas Algeria Department of Electrical and Computer Engineering University of Sharjah UAE

In this work, we introduce a new approach for the signal deconvolution problem, which is useful for the enhancement of neutron radiography projections. We attempt to restore original signals and get rid of noise present during acquisition or processing, due to gamma radiations or randomly distributed neutron flux. Signal deconvolution is an ill-posed inverse problem, so regularization techniques are used to smooth solutions by imposing constraints in the objective function. Various popular algorithms have been developed to solve such problem. This paper proposes a new approach to the nonlinear degraded signals restoration which is useful in many signal enhancement applications, based on a synergy of two swarm intelligence algorithms: particle swarm optimization (PSO) and bacterial foraging optimization (BFO) applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method. We attempt to reconstruct or recover signals using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition and the wavelet filtering methods are also considered in this paper. A comparison between several powerful techniques is conducted.

关键词： Noise Microorganisms image restoration Deconvolution Optimization Nonlinear filters

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A thresholding method based on P systems for image segmentation

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ICIC Express Letters 2012年第1期6卷 221-227页

作者： Wang, Hao Peng, Hong Shao, Jie Wang, Tao School of Mathematics and Computer Engineering Xihua University Chengdu 610039 China School of Electrical and Information Engineering Xihua University Chengdu 610039 China

Membrane computing is a novel class of distributed parallel computing models. Application of membrane computing to image processing is an interesting topic. In this paper, we propose a thresholding method based on P systems for image segmentation. A two-layer tissue-like P system with symport/antiport rules is designed as its computing device and it includes two kinds of rules: evolution rules and communication rules. The evolution rules use three standard evolution operators (selection, crossover and mutation), while communication rules are used to exchange and share information between the membranes. After the computation halts, optimal segmentation threshold will be provided by skin membrane. Experimental results on several standard images illustrate the applicability and effectiveness of the proposed thresholding method for image segmentation, and meanwhile we give comparison results of the proposed thresh holding method with other methods. © 2012 ISSN 1881-803X.

关键词： Tissue

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A Novel Associative Model of Data: Toward a distributed Large-Scale Data processing Scheme for Future Computer Clouds

A Novel Associative Model of Data: Toward a Distributed Larg...

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IEEE International Symposium on Network Computing and Applications

作者： Amir H. Basirat Asad I. Khan Clayton School of IT Monash University Melbourne Australia

Existing cloud frameworks involve isolating low-level operations within an application for data distribution and partitioning. This limits their applicability for many applications with complex data dependency considerations. This paper aims to explore new methods of partitioning and distributing data in the cloud by fundamentally re-thinking the way in which future data management models will need to be developed on the Internet. Loosely-coupled associative computing techniques, which have so far not been considered, can provide the break-through needed for a distributed data management scheme. Using a novel lightweight associative memory algorithm known as Edge Detecting Hierarchical Graph Neuron (Edge HGN), data retrieval/processing can be modeled as a pattern recognition problem, conducted across multiple records within a single-cycle, utilizing a parallel approach. The proposed model envisions a distributed data management scheme for large-scale data processing and database updating that is capable of providing scalable real-time recognition and processing with high accuracy while being able to maintain low computational cost in its function.

关键词： Pattern recognition image edge detection Neurons distributed databases Arrays Accuracy Associative memory

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Evaluation and comparison of cell nuclei detection algorithms

Evaluation and comparison of cell nuclei detection algorithm...

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IEEE International Conference on Intelligent Engineering Systems (INES)

作者： Sándor Szénási Zoltán Vámossy Miklós Kozlovszky Doctoral School of Applied Informatics Óbuda University Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Budapest Hungary Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary

The processing of microscopic tissue images and especially the detection of cell nuclei is nowadays done more and more using digital imagery and special immunodiagnostic software products. Since several methods (and applications) were developed for the same purpose, it is important to have a measuring number to determine which one is more efficient than the others. The purpose of the article is to develop a generally usable measurement number that is based on the “gold standard” tests used in the field of medicine and that can be used to perform an evaluation using any of image segmentation algorithms. Since interpreting the results themselves can be a pretty time consuming task, the article also contains a recommendation for the efficient implementation and a simple example to compare three algorithms used for cell nuclei detection.

关键词： Accuracy Algorithm design and analysis image segmentation Time measurement Gold Standards Classification algorithms

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基于分布式多图像处理器的医学影像体绘制算法

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中国医学装备 2012年第8期9卷 4-7页

作者：商洪涛唐辉徐涛北京军区总医院医学工程科北京100700

目的:计算机医学图像处理具有所需计算量和计算涉及数据量巨大的特点,需将高性能计算技术应用于计算机医学图像处理中,以适应计算涉及数据量大和计算速度快的要求。方法:计算统一设备架构(CUDA)技术可使图像处理单元(GPU)进行通用并行计... 详细信息

目的:计算机医学图像处理具有所需计算量和计算涉及数据量巨大的特点,需将高性能计算技术应用于计算机医学图像处理中,以适应计算涉及数据量大和计算速度快的要求。方法:计算统一设备架构(CUDA)技术可使图像处理单元(GPU)进行通用并行计算,使其能够提供强大的计算能力。由于分布式并行计算是实现高性能计算的主要方式,故提出一种实用的分布式并行计算模式,即基于分布式多GPU的并行计算模式,其中多台计算机将使用消息传递接口(MPI)并行编程环境配置成分布式集群系统。结果:以医学影像体绘制算法为例分析该计算模式,使得其算法计算时间较短,计算效率较高。结论:使用MPI集群和GPU进行算法加速,可很好地解决无法实现医学影像的实时三维重建的问题。

关键词：分布式多图像处理单元光线投射体绘制医学影像处理算法

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