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检索条件"任意字段=Conference on Parallel Processing for Imaging Applications"

共 765 条记录，以下是91-100 订阅

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parallel implementation of skeleton-based pedestrian tracking on a Cell Broadband Engine processor

Parallel implementation of skeleton-based pedestrian trackin...

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8th IASTED International conference on Visualization, imaging, and Image processing, VIIP 2008

作者： Sugano, Hiroki Nakamura, Yukihiro Shinoda, Tomonori Miyamoto, Ryusuke Dept. of Communications and Computer Engineering Kyoto University Yoshida-hon-machi Sakyo Kyoto 606-8501 Japan Research Organization of Science and Engineering Ritsumeikan University 1-1-1 Noji-Higashi Kusatsu Shiga 525-8577 Japan Dept. of Information Systems Nara Institute of Science and Technology 8916-5 Takayama-cho Ikoma Nara Japan

ISBN: (纸本)9780889867598

Currently we must realize a pedestrian recognition system based on image processing for embedded applications, such as automotive applications, surveillance, and robotics. In these applications, highly accurate recognition must be achieved with real-time processing under limited system resources. To achieve such a pedestrian recognition system, we implement a skeleton-based pedestrian tracking scheme which can track pedestrians accurately on Cell Broadband Engine (CBE), one of the latest high performance embedded processors for general purpose use, which has a novel memory management system to achieve efficient computation with parallel execution units. Experimental results using a test sequence show that processing time is reduced drastically when the number of SPE used for computation increases.

关键词： Image processing

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Resolution Enhancement Using parallel Computing

Resolution Enhancement Using Parallel Computing

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International conference on Intelligent and Advanced Systems

作者： Patil, Varsha H. Bormane, Dattatraya S. Kharate, Gajanan K. Dept. of Computer Engg. KKWIEER Nashik India Rajashree Shahu College of Engineering Pune(MS) India IT Department KKWIEER Nashik(MS) India

ISBN: (纸本)9781424413553

High resolution digital imaging has been one of the most important developments in image processing over last decade. Constructing high resolution image using one or more shifted low resolution images of same scene is referred as super resolution imaging. Super resolution imaging involves registering the input low resolution images and then interpolation to construct high resolution image. Appropriate interpolation plays an important role in super resolution imaging. Wavelet transform has come up as proven valuable tool for super resolution imaging along with other image processing applications. In this paper we have addressed the use and computational cost of wavelets. We take in hand grid based parallel implementation of wavelet based interpolation and put forward for super resolution imaging as a promising solution to speed up the super resolution imaging process. Simulation results support the claim of four time faster interpolation as compared to conventional methods along with good quality.

关键词： Interpolation

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An Intelligent parallel Distributed Streaming Framework for near Real-time Science Sensors and High-Resolution Medical Images 21

An Intelligent Parallel Distributed Streaming Framework for ...

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50th International conference on parallel processing (ICPP)

作者： Shivadekar, Samit Mangalagiri, Jayalakshmi Phuong Nguyen Chapman, David Halem, Milton Gite, Rahul Univ Maryland Baltimore Cty Baltimore MD 21228 USA OpenKneck Inc Halethorpe MD USA

ISBN: (纸本)9781450384414

Our goals are to address challenges such as latency, scalability, throughput and heterogeneous data sources of streaming analytics and deep learning pipelines in science sensors and medical imaging applications. We present a prototype Intelligent parallel Distributed Streaming Framework (IPDSF) that is capable of distributed streaming processing as well as performing distributed deep training in batch mode. IPDSF is designed to run streaming Artificial Intelligent (AI) analytic tasks using data parallelism including partitions of multiple streams of short time sensing data and high-resolution 3D medical images, and fine grain tasks distribution. We will show the implementation of IPDSF for two real world applications, (i) an Air Quality Index based on near real time streaming of aerosol Lidar backscatter and (ii) data generation of Covid-19 Computing Tomography (CT) scans using deep learning. We evaluate the latency, throughput, scalability, and quantitative evaluation of training and prediction compared against a baseline single instance. As the results, IPDSF scales to process thousands of streaming science sensors in parallel for Air Quality Index application. IPDSF uses novel 3D conditional Generative Adversarial Network (cGAN) training using parallel distributed Graphic processing Units (GPU) nodes to generate realistic 3D high resolution Computed Tomography scans of Covid-19 patient lungs. We will show that IPDSF can reduce cGAN training time linearly with the number of GPUs.

关键词： Distributed streaming Data parallelism Deep Learning Lidar backscatter Computed Tomography cGAN

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Hadoop-based Implementation of processing Medical Diagnostic Records for Visual Patient System

Hadoop-based Implementation of Processing Medical Diagnostic...

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conference on Medical imaging - imaging Informatics for Healthcare, Research, and applications

作者： Yang, Yuanyuan Shi, Liehang Xie, Zhe Zhang, Jianguo Chinese Acad Sci Shanghai Inst Tech Phys Lab Med Imaging Informat Beijing Peoples R China

ISBN: (数字)9781510616486

ISBN: (纸本)9781510616486

We have innovatively introduced Visual Patient (VP) concept and method visually to represent and index patient imaging diagnostic records (IDR) in last year SPIE Medical imaging (SPIE MI 2017), which can enable a doctor to review a large amount of IDR of a patient in a limited appointed time slot. In this presentation, we presented a new approach to design data processing architecture of VP system (VPS) to acquire, process and store various kinds of IDR to build VP instance for each patient in hospital environment based on Hadoop distributed processing structure. We designed this system architecture called Medical Information processing System (MIPS) with a combination of Hadoop batch processing architecture and Storm stream processing architecture. The MIPS implemented parallel processing of various kinds of clinical data with high efficiency, which come from disparate hospital information system such as PACS, RIS LIS and HIS.

关键词： Hadoop Visual Patient PACS RIS

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INTERFACING A RADIOLOGY INFORMATION-SYSTEM AND A PICTURE ARCHIVING AND COMMUNICATION-SYSTEM

INTERFACING A RADIOLOGY INFORMATION-SYSTEM AND A PICTURE ARC...

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IEEE PACIFIC RIM CONF ON COMMUNICATIONS COMPUTER AND SIGNAL processing

作者： SOEHLKE, K ATKINSON, J FISHER, P Sch of Health Inf Sci Univ of Victoria BC Canada

ISBN: (纸本)0879426381

In some medical imaging (MI) departments two information systems have developed in parallel, a radiology information management system (RIMS) and a picture archiving and communication system (PACS). A connection between the two applications is required to adequately support the medical imaging process and is vital to a completely digital MI department. The RIMS-PACS interface will provide the mechanism for single-point access to all of the information required by a radiologist for a diagnosis. The authors describe the results of the analysis of the two systems and outline possibilities for their interconnection. The high-level design of the RIMS-PACS interface as reported will satisfy the clinical users' need for single-point access to the data required for clinical radiology. It overcomes the obstacles presented by the low connectivity of the two applications. The complexity of the analysis required to design the interface highlights the need for more strategic planning before information systems are implemented.

关键词： Image processing

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parallel implementation of an iterative PCA algorithm for hyperspectral images on a manycore platform

Parallel implementation of an iterative PCA algorithm for hy...

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conference on Design and Architectures for Signal and Image processing (DASIP)

作者： Lazcano, R. Madronal, D. Fabelo, H. Ortega, S. Salvador, R. Callico, G. M. Juarez, E. Sanz, C. Univ Politecn Madrid Ctr Software Technol & Multimedia Syst CITSEM Madrid Spain ULPGC Res Inst Appl Microelect IUMA Las Palmas Gran Canaria Spain

ISBN: (纸本)9781538635346

This paper presents a study of the parallelization possibilities of a Non-Linear Iterative Partial Least Squares algorithm and its adaptation to a Massively parallel Processor Array manycore architecture, which assembles 256 cores distributed over 16 clusters. The aim of this work is twofold: first, to test the behavior of iterative, complex algorithms in a manycore architecture;and, secondly, to achieve real-time processing of hyperspectral images, which is fixed by the image capture rate of the hyperspectral sensor. Real-time is a challenging objective, as hyperspectral images are composed of extensive volumes of spectral information. This issue is usually addressed by reducing the image size prior to the processing phase itself. Consequently, this paper proposes an analysis of the intrinsic parallelism of the algorithm and its subsequent implementation on a manycore architecture. As a result, an average speedup of 13 has been achieved when compared to the sequential version. Additionally, this implementation has been compared with other state-of-the-art applications, outperforming them in terms of performance.

关键词： NIPALS-PCA Hyperspectral imaging Massively parallel processing Real-time processing

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Block rotation: Implementation and applications

Block rotation: Implementation and applications

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conference on parallel and Distributed Methods for Image processing

作者： Fatemi, O Panchanathan, S Univ. of Ottawa (Canada) Univ. of Ottawa (United States)

ISBN: (纸本)0819425885

Visual media processing is becoming increasingly important because of the wide variety of image and video based applications. Block rotation is an important operation in different image/video processing tasks such as graphics, fractal processing, pattern matching and image registration. Remote sensing, medical imaging, computer vision, computer graphics, and video coding are typical applications of digital image rotation. However, a hardware implementation of the block rotation algorithm has not been realized and software implementation is slow. Hence, they are not suitable for real-time execution. In this paper, we propose a novel method for block rotation, which is fast and suitable for hardware implementation. The algorithm employs area based interpolation. Experimental results have shown the performance enhancement compared to classical interpolation algorithms at a similar level of complexity.

关键词： image rotation spatial transformation affine transform interpolation forward mapping and backward mapping

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Reconfigurable HW-SW Co-design Platform for Lung Cancer Detection and Classification 34

Reconfigurable HW-SW Co-design Platform for Lung Cancer Dete...

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34th International conference on VLSI Design / 20th International conference on Embedded Systems (VLSID)

作者： Sharma, Ayushparth Lata, Kusum LNM Inst Informat Technol Jaipur Rajasthan India

ISBN: (纸本)9781665440875

High-performance electronics has fueled the rich emergence of medical imaging applications that led to the exponential growth in treatment and diagnostic solutions of various medical problems. High-throughput and Energy-efficient systems are required to enable the development of complex medical imaging applications. This article presents an energy-efficient hardware-software (HW-SW) co-design of a scalable and reconfigurable image segmentation/classification streaming-based processing platform explored at various design abstraction levels. Optimized algorithms and architectural techniques achieve significant savings in energy consumption and operational time. The proposed platform has been implemented on Xilinx Spartan-6 FPGA board and co-simulated with Xilinx system generator, enabled real-time processing of CT scans for pulmonary nodule detection. Optimized pipelining and scheduling have minimized the memory requirements to few kB. parallel architecture has been employed achieving 10x higher energy-efficiency compared to serial counterpart and reduced execution period by 70x. Clinical validation shows that parallel architecture introduces 5-7% error in nodule characteristic determination in comparison to serial one.

关键词： lung cancer detection delay structures medical image processing energy-efficient platform reconfigurability

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Multiple-GPU Accelerated Range-Doppler Algorithm for Synthetic Aperture Radar imaging

Multiple-GPU Accelerated Range-Doppler Algorithm for Synthet...

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IEEE Radar conference (RADAR)

作者： Ning, Xia Yeh, Chunmao Zhou, Bin Gao, Wei Yang, Jian Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781424489022

parallelization based on general purpose graphic processing unit (GPGPU) is a kind of promising technology widely used to improve the computing performance. GPU is designed for data parallel and computational intensive applications. In this paper, a data processor based on multiple GPGPU devices is proposed for SAR signal processing. Some key technologies are emphasized for exploiting the best performance of GPGPU. And the processor's performance is demonstrated by the implementation of range-Doppler imaging algorithm, which shows it is suitable for real-time SAR signal processing.

关键词： Algorithm design and analysis Apertures GPGPU devices Graphics processing unit Instruction sets Performance evaluation Signal processing algorithms Synthetic aperture radar computational intensive application computer graphic equipment coprocessors data p

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parallel and Cloud-based Analysis of Omics Data: Modelling and Simulation in Medicine 25

Parallel and Cloud-based Analysis of Omics Data: Modelling a...

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25th Euromicro International conference on parallel, Distributed and Network-Based processing (PDP)

作者： Agapito, Giuseppe Calabrese, Barbara Guzzi, Pietro H. Fragomeni, Gionata Tradigo, Giuseppe Veltri, Pierangelo Cannataro, Mario Magna Graecia Univ Catanzaro Dept Med & Surg Sci Catanzaro Italy

ISBN: (纸本)9781509060580

High throughput experimental platforms and diagnostic equipments available in clinical settings and in research laboratories, such as magnetic resonance imaging, microarray, mass spectrometry and next-generation sequencing, are producing an increasing volume of clinical and omics data. Moreover, Electronic Patients Records (EPRs), eHealth systems, personal mobile sensors and Social Networks are collecting an overwhelming volume of health and life style data that may be integrated with clinical data and more and more is used for the real-time monitoring of patient's health. This poses new issues in terms of secure data storage, effective models for data integration, efficient algorithms for data analysis, new models for health monitoring, that may be addressed, among the others, using high performance computing solutions. parallel computing and Cloud Computing may offer efficient and scalable solutions in an orthogonal way. In fact, parallel, bioinformatics software, that exploit off-the-shelf high performance computers, may be used to preprocess and analyze omics data at a lower layer, for instance to highlight genetic variation associated with complex diseases. On the other hand, Cloud Computing offers large scale data storage, data sharing services, on-demand anytime and anywhere access to resources and applications, for the realization of elastic and scalable applications and services. Motivated by the increasing use of parallel computing and cloud computing in life sciences, in this paper we survey both parallel bioinformatics algorithms for the parallel preprocessing and statistical and data mining analysis of omics data, as well as Cloud-based healthcare and biomedicine services and systems for large scale applications. Moreover, the paper underlines main issues and problems related to the use of such platforms for the storage and analysis of health data, with special focus to the security and privacy of patients data, that are particularly important in fields

关键词： Data visualization Bioinformatics Cloud computing Biological system modeling Proteins Genomics

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