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A Survey of Medical image Registration on Multicore and the GPU

IEEE SIGNAL processing MAGAZINE 2010年第2期27卷 50-60页

作者： Shams, Ramtin Sadeghi, Parastoo Kennedy, Rodney A. Hartley, Richard I. College of Engineering and Computer Science at the Australian National University (ANU).

In this article, we look at early, recent, and state-of-the-art methods for registration of medical images using a range of high-performance computing (HPC) architectures including symmetric multiprocessing (SMP), massively multiprocessing (MMP), and architectures with distributed memory (DM), and nonuniform memory access (NUMA). The article is designed to be self-sufficient. We will take the time to define and describe concepts of interest, albeit briefly, in the context of image registration and HPC. We provide an overview of the registration problem and its main components in the section "Registration." Our main focus will be HPC-related aspects, and we will highlight relevant issues as we explore the problem domain. This approach presents a fresh angle on the subject than previously investigated by the more general and classic reviews in the literature [1]-[3]. The sections "Multi-CPU Implementations" and "Accelerator Implementations" are organized from the perspective of high-performance and parallel- computing with the registration problem embodied. This is meant to equip the reader with the knowledge to map a registration problem to a given computing architecture.

关键词： Biomedical imaging image registration Multicore processing Surges Computer architecture Cancer Ultrasonic imaging Computed tomography Pancreas Laparoscopes

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DESIGN OF TWO-DIMENSIONAL INFINITE IMPULSE RESPONSE RECURSIVE FILTERS USING HYBRID MULTIAGENT PARTICLE SWARM OPTIMIZATION

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APPLIED ARTIFICIAL INTELLIGENCE 2010年第4期24卷 295-312页

作者： Kumar, Rajesh Kumar, Anupam Malaviya Natl Inst Technol Dept Elect Engn Jaipur Rajasthan India

We incorporate the optimization problem of two-dimensional infinite impulse response (IIR) recursive filters and the optimization methodology of hybrid multiagent particle swarm optimization (HMAPSO) and then apply the resultant optimized IIR filter in image processing for justifying HMAPSO robustness over other algorithm and its role in optimizing real-time situations. The design of the 2-D IIR filter is reduced to a constrained minimization problem whose robust solution is being achieved by a novel and optimal algorithm HMAPSO. This algorithm integrates the deterministic solution by the multiagent system, the particle swarm optimization (PSO) algorithm, and bee decision-making process. All agents search parallel in an equally distributed lattice-like structure to save energy and computational time as done by the bees in their hive selection process. Thus making use of deterministic search, multiagent PSO, and bee, the HMAPSO realizes the purpose of optimization. Experimental results and the application of the designed filters to focusing the defocused image show that the HMAPSO approach provides better upshots than the previous design methods.

关键词： image processing Robust solution HYBRID Infinite Impulse Response design approach computational time IMPULSE RESPONSE Infinite impulse response filters recursive filters Process selection Bee

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On the parallelisation of MCMC-based image processing

On the parallelisation of MCMC-based image processing

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2010 IEEE International Symposium on parallel and distributed processing, Workshops and Phd Forum, IPDPSW 2010

作者： Byrd, Jonathan M. R. Jarvis, Stephen A. Bhalerao, Abhir H. Department of Computer Science University of Warwick Coventry CV4 7AL United Kingdom

ISBN: (纸本)9781424465347

The increasing availability of multi-core and multi-processor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As such MCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. Whilst divide and conquer is an obvious means to simplify image processing tasks, "naively" dividing an image into smaller images to be processed separately results in anomalies and breaks the statistical validity of the MCMC algorithm. We present a method of grouping the spatially local moves and temporarily partitioning the image to allow those moves to be processed in parallel, reducing the runtime whilst conserving the properties of the MCMC method. We calculate the theoretical reduction in runtime achievable by this method, and test its effectiveness on a number of different architectures. Experiments are presented that show reductions in runtime of 38% using a dual-core dual-processor machine. In circumstances where absolute statistical validity are not required, an algorithm based upon, but not strictly adhering to, MCMC may suffice. For such situation two additional algorithms are presented for partitioning of images to which MCMC will be applied. Assuming preconditions are met, these methods may be applied with minimal risk of anomalous results. Although the extent of the runtime reduction will be data dependent, the experiments performed showed the runtime reduced to 27% of its original value.© 2010 IEEE.

关键词： image processing

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Novel wavelength diversity technique for high speed atmospheric turbulence compensation

Novel wavelength diversity technique for high speed atmosphe...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C31) Technologies for Homeland Security and Homeland Defense IX

作者： Arrasmith, William W. Sullivan, Sean F. Florida Inst Technol Melbourne FL 32901 USA

ISBN: (纸本)9780819481306

The defense, intelligence, and homeland security communities are driving a need for software dominant, real-time or near-real time atmospheric turbulence compensated imagery. The development of parallel processing capabilities are finding application in diverse areas including image processing, target tracking, pattern recognition, and image fusion to name a few. A novel approach to the computationally intensive case of software dominant optical and near infrared imaging through atmospheric turbulence is addressed in this paper. Previously, the somewhat conventional wavelength diversity method has been used to compensate for atmospheric turbulence with great success. We apply a new correlation based approach to the wavelength diversity methodology using a parallel processing architecture enabling high speed atmospheric turbulence compensation. methods for optical imaging through distributed turbulence are discussed, simulation results are presented, and computational and performance assessments are provided.

关键词： horizontal path imaging adaptive optics image reconstruction deconvolution autocorrelation turbulence compensation image processing.

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Optimizing algebraic and neural methods for information processing in distributed fiber-optical measuring systems

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Optical Memory and Neural Networks (Information Optics) 2010年第3期19卷 237-247页

作者： Kulchin, Yu.N. Zakasovskaya, E.V. Institute for Automation and Control Processes FEB RAS ul. Radio 5 Vladivostok 690041 Russia Far-Eastern State University 8 Suhanova st. 690000 Vladivostok Russia

The paper discusses tomography reconstruction of distributed physical fields by means of fiber optical measuring systems (FOMN) [1] for parallel setup of measuring lines with a small number of scanning directions. The approach whose novelty involves measuring network geometry optimization for further application of neural or algebraic technologies to restore a full image of the functions studied is presented. An alternative to choose and apply an appropriate neural network from the set of several, previously trained neural networks of radial-basic type is investigated [2]. © 2010 Allerton Press, Inc.

关键词： Radial basis function networks

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The Java image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

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NEUROINFORMATICS 2010年第1期8卷 5-17页

作者： Lucas, Blake C. Bogovic, John A. Carass, Aaron Bazin, Pierre-Louis Prince, Jerry L. Pham, Dzung L. Landman, Bennett A. Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA NIA NIH Baltimore MD 21224 USA Johns Hopkins Univ Dept Radiol & Radiol Sci Baltimore MD 21218 USA Vanderbilt Univ Dept Elect Engn Nashville TN 37235 USA Vanderbilt Univ Dept Radiol & Radiol Sci Nashville TN 37235 USA

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

关键词： parallel processing Pipeline Rapid prototyping image processing MRI

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Regularization parameter estimation for large-scale Tikhonov regularization using a priori information

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2010年第12期54卷 3430-3445页

作者： Renaut, Rosemary A. Hnetynkova, Iveta Mead, Jodi Arizona State Univ Dept Math & Stat Tempe AZ 85287 USA

Solutions of numerically ill-posed least squares problems Ax approximate to b for A is an element of R-mxn by Tikhonov regularization are considered. For D is an element of R-pxn, the Tikhonov regularized least squares functional is given by J(sigma) = parallel to Ax - b parallel to(2)(W) + 1/sigma(2) parallel to D(x - x(0))parallel to(2)(2) where matrix W is a weighting matrix and x(0) is given. Given a priori estimates on the covariance structure of errors in the measurement data b, the weighting matrix may be taken as W = W-b which is the inverse covariance matrix of the mean 0 normally distributed measurement errors e in b. If in addition x(0) is an estimate of the mean value of x, and sigma is a suitable statistically-chosen value, J evaluated at its minimizer x(sigma) approximately follows a chi(2) distribution with (m) over tilde = m + p - n degrees of freedom. Using the generalized singular value decomposition of the matrix pair [W(b)(1/2)AD], sigma can then be found such that the resulting J follows this chi(2) distribution. But the use of an algorithm which explicitly relies on the direct solution of the problem obtained using the generalized singular value decomposition is not practical for large-scale problems. Instead an approach using the Golub-Kahan iterative bidiagonalization of the regularized problem is presented. The original algorithm is extended for cases in which x(0) is not available, but instead a set of measurement data provides an estimate of the mean value of b. The sensitivity of the Newton algorithm to the number of steps used in the Golub-Kahan iterative bidiagonalization, and the relation between the size of the projected subproblem and sigma are discussed. Experiments presented contrast the efficiency and robustness with other standard methods for finding the regularization parameter for a set of test problems and for the restoration of a relatively large real seismic signal. An application for image deblurring also validates the appr

关键词： PARAMETER estimation INFORMATION processing LEAST squares FUNCTIONAL analysis STATISTICS DATA analysis

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Scalability in privacy-preserving data aggregation for wireless sensor networks

Scalability in privacy-preserving data aggregation for wirel...

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IEEE International Symposium on parallel and distributed processing With Applications

作者： Bista, Rabindra Shin, Young-Sung Chang, Jae-Woo Dept. of Computer Engineering Center for Advanced Image and Information Technology Chonbuk National University Chonju Chonbuk 561-756 Korea Republic of

ISBN: (纸本)9780769541907

In this paper, we propose a new privacy preserving data aggregation scheme for WSNs. Our scheme applies additive property of complex numbers in order to combine sensor data and preserve data privacy during transmission to the sink node. In addition, for supporting scalability, we propose a novel mechanism in which a special set of real numbers are assigned to sensor nodes as their IDs so that a single bit is sufficient to hold ID of a sensor node during transmission of aggregated data to the sink node. For this, we, first, generate fixed size signatures for the IDs of all sensor nodes and then superimpose the signatures during data aggregation phase. By analytical evaluations, we show that our scheme is more scalable and energy efficient than the existing methods to achieve data privacy and transmit IDs of sensor nodes along with the aggregated data to the sink node. © 2010 IEEE.

关键词： Sensor nodes

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Low cost VLSI discrete wavelet transform and FIR filters architectures for very high-speed signal and image processing

Low cost VLSI discrete wavelet transform and FIR filters arc...

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作者： Maamoun, Mountassar Bradai, Rafik Meraghni, Abdelhamid Beguenane, Rachid Department of Electronics University of Blida Blida Algeria Kouba Algeria Department of Electrical Computer Engineering Royal Military College of Canada Kingston Canada

ISBN: (纸本)9781424490233

This paper presents new VLSI architectures for finite impulse response (FIR) filters and discrete wavelet transform, intended for very high-speed signal and image processing. The proposed architectures, based on combining pipeline and parallel arithmetic methods, provide a new and very fast convolution approach with a reduced critical path. The key to this is a clever use of D-latches and multipliers which are efficiently distributed. Furthermore, an advanced discrete wavelet transform (DWT) approach, with an area-efficient architecture, is designed to produce one output in every clock cycle. As a result, a very high-speed is attained. The proposed structure can increase the work frequency (85%) at a low cost of additional hardware elements (55%). The systems are verified, using JPEG2000 coefficients filters, on Xilinx Field Programmable Gate Array (FPGA) devices. © 2010 IEEE.

关键词： FIR filters

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Integration of gpgpu methods into a pet reconstruction system

Integration of gpgpu methods into a pet reconstruction syste...

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9th IASTED International Conference on parallel and distributed Computing and Networks, PDCN 2010

作者： Schaetz, Sebastian Kucera, Markus Department of Computer Science and Mathematics University of Applied Sciences Regensburg Germany

ISBN: (纸本)9780889868205

Positron emission tomography (PET) is a medical imaging modality that allows the detection of tissue with particular properties or the observation of metabolic processes in living organisms over time. It plays a vital role in cancer diagnosis and heart examination and represents a promising method for early diagnosis of dementia. With the advancement of scanner technology as well as an ever increasing demand for higher quality images and higher patient throughput the image reconstruction system can become a bottleneck of a PET system. To meet this demand for more computing power in the reconstruction system a novel way to speed up the image reconstruction process for modern PET systems is presented. A common graphics processing device in conjunction with the Compute Unified Device Architecture (CUDA) is used to speed up existing algorithms for the CPU. Projectors for full 3D reconstruction are ported to the CUDA device and new algorithms are implemented where necessary. The main focus of this port is to speed up the calculation and to maintain the numerical accuracy of the result. On the basis of the CPU reconstruction system a new system that uses GPU projectors is implemented. With this modification a two-fold speed up is achieved compared to the highly optimized CPU implementation running on 4 CPU cores. Different optimization methods are explored and applied where suitable. The results calculated by GPU and CPU projectors are numerically identical allowing them to be interchanged. The system is validated and the algorithms are integrated into the reconstruction system of Siemens Healthcare Molecular Imaging PET scanners.

关键词： Three dimensional

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