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International conference on Electronics, Materials Engineering and Nano-Technology (IEMENTech)

作者： Samit Karmakar Arindam Chakraborty Saptarshi Banerjee Ayantika Mondal Satavisha Dutta Sayak Nandi Electronics & Communication Engineering Dept. Institute of Engineering & Management University of Engineering & Management Kolkata India

ISBN: (数字)9798331520762

ISBN: (纸本)9798331520779

Medical image segmentation is a critical process in identifying disease-infected regions for diagnostic and treatment purposes. This paper introduces an FPGA-based framework for implementing the Expectation Maximization/Markov Random Field (E M/MP M) algorithm in 3D medical image segmentation. FPGA platforms offer unparalleled advantages in terms of parallel processing, speed, and energy efficiency, making them a promising choice for real-time medical image analysis. This proposed framework enables rapid segmentation of 3D images, leveraging the FPGA's on-chip memory and custom logic for efficient pixel classification and data processing. The adaptive design also supports the integration of external RAM for larger datasets. Simulated using Verilog HDL and Quartus Prime, this work demonstrates accurate segmentation results through virtual testing, thus showcasing the system's robustness for medical applications.

关键词： Image segmentation Three-dimensional displays Random access memory Medical services parallel processing Real-time systems Energy efficiency Hardware design languages Medical diagnostic imaging Field programmable gate arrays

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Advancements in Real-Time Image processing Using Kintex and Virtex FPGAs: Enhancing Speed, Efficiency, and Versatility

Advancements in Real-Time Image Processing Using Kintex and ...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE conference on

作者： Shishir Shrivastava Bura Vijay Kumar Rupesh Gupta Vibhor Sharma Institute of Engineering and Technology Chitkara University School of Computer Science and Artificial Intelligence SR University Warangal Telangana India University of New Haven

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Image processing is a critical component in various applications, ranging from medical imaging to autonomous systems. This research explores the utilization of high-performance Field Programmable Gate Arrays (FPGAs) such as Kintex and Virtex to enhance image processing capabilities. By leveraging the parallel processing power and reconfigurability of these FPGAs, the study achieves significant improvements in processing speed and efficiency, enabling real-time image analysis and decision-making. This advancement supports the United Nations’ Sustainable Development by enhancing smart city technologies. The implementation of Kintex and Virtex in image processing not only drives innovation but also contributes to building resilient and sustainable infrastructures, thereby promoting well-being and sustainable urban development.

关键词： Technological innovation Smart cities Autonomous systems Image processing Scalability Decision making Real-time systems Distance measurement Sustainable development Field programmable gate arrays

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Optimization of Memory Usage in High-Speed Cameras using FPGA

Optimization of Memory Usage in High-Speed Cameras using FPG...

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Electronics and Renewable Systems (ICEARS), International conference on

作者： Kavin Kumar K Neelam Sanjeev Kumar Senthilkumar C Velmurugan V G Sangar Gokul Chandrasekaran Department of Electronics and Communication Engineering Kongu Engineering College Erode India Department of Computer Science and Engineering (E.Tech.) SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering SIMATS Engineering SIMATS University Chennai Tamil Nadu Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

High-speed cameras generate large amounts of data, making memory optimization difficult for real-time processing. This project minimizes data size by converting RGBA (Red, Green, Blue, Alpha) images to RGB, eliminating the Alpha channel to reduce memory usage. The captured images are provided as input to Verilog code in hexadecimal format, with the conversion done by MATLAB. Bilinear Interpolation is applied to reduce the potential quantization errors during the conversion, using the values of four surrounding pixels to smooth the image and maintain quality. After processing, the image is reconstructed using MATLAB, ensuring the integrity of the output. By utilizing the parallel processing capabilities of FPGAs, this method ensures real-time performance while optimizing memory usage. It is ideal for high-speed imaging applications where both efficiency and image quality are crucial.

关键词： Interpolation Renewable energy sources Quantization (signal) Memory management parallel processing Cameras Real-time systems MATLAB Field programmable gate arrays Optimization

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Advancing Healthcare with GPGPU and Energy Efficient NoC Architectures: A Comprehensive Survey

Advancing Healthcare with GPGPU and Energy Efficient NoC Arc...

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Ambient Intelligence in Health Care (ICAIHC), International conference on

作者： Panthagani Vijaya Babu Sonal Yadav Vijay Holimath Dept. of Computer Science & Engineering ViBram Silicon Hub National Institute of Technology Raipur India VividSparks IT Solutions Bangalore India

ISBN: (数字)9798331530259

ISBN: (纸本)9798331530266

General-purpose Graphics processing Units (GPGPU) have emerged as a transformative technology in healthcare and medical fields, harnessing their powerful parallel processing capabilities to handle complex computational challenges. Initially developed for graphics rendering, GPUs are now employed in high-performance tasks such as medical imaging, genomic analysis, drug discovery, and real-time patient monitoring, where vast data volumes and intensive computations are prevalent. GPGPU technology enhances processing efficiency, reduces latency, and supports faster, more accurate diagnostics and treatment planning. Complementing this advancement, Networks-On-Chip (NoC) designs, introduced in the early 2000s, have become a standard communication backbone for high-end CPUs and Systems-on-Chip (SoCs). Their low communication latency, high throughput, and energy efficiency make NoCs ideal for addressing the growing demands of GPU-based systems. However, achieving these performance objectives requires minimizing power dissipation, energy consumption, and costs. This research provides a comprehensive survey of NoC design models for multi-GPU systems, focusing on their role in energy-efficient and scalable architectures. It also highlights the impact of GPGPU in revolutionizing healthcare by meeting modern medical applications' computational and efficiency requirements.

关键词： Surveys Scalability Memory management Graphics processing units Medical services Throughput Energy efficiency Real-time systems Computational efficiency Standards

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parallel Approaches to Digital Signal processing Algorithms with applications in Medical imaging 13

Parallel Approaches to Digital Signal Processing Algorithms ...

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13th IEEE International conference on Signal processing and Communication Systems (ICSPCS)

作者： Kapinchev, Konstantin Bradu, Adrian Podoleanu, Adrian Univ Kent Sch Comp Sch Phys Sci Canterbury Kent England Univ Kent Appl Opt Grp Sch Phys Sci Canterbury Kent England

ISBN: (纸本)9781728121949

This paper reviews established and emerging parallel technologies, which are employed to enhance the performance of digital signal processing algorithms. Special attention is paid to algorithms with applications in medical imaging. parallel implementations of some of the most commonly used algorithms, such as Fourier transforms, convolution and cross-correlation are discussed. parallel optimization of a newly introduced method in optical coherence tomography is presented. Its performance, in terms of latency, is presented and discussed.

关键词： parallel computing digital signal processing medical imaging optical coherence tomography

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parallel stereocorrelation on a reconfigurable multi-ring network

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JOURNAL OF SUPERCOMPUTING 1996年第3期10卷 243-269页

作者： Arabnia, HR Bhandarkar, SM Department of Computer Science University of Georgia 415 Boyd Graduate Studies Research Center Athens USA

A reconfigurable network termed as the reconfigurable multi-ring network (RMRN) is described. The RMRN is shown to be a truly scalable network in that each node in the network has a fixed degree of connectivity and the reconfiguration mechanism ensures a network diameter of O(log(2) N) for an N-processor network. Algorithms for the two-dimensional mesh and the SIMD or SPMD n-cube are shown to map very elegantly onto the RMRN. Basic message passing and reconfiguration primitives for the SIMD/SPMD RMRN are designed for use as building blocks for more complex parallel algorithms. The RMRN is shown to be a viable architecture for image processing and computer vision problems using the parallel computation of the stereocorrelation imaging operation as an example. Stereocorrelation is one of the most computationally intensive imaging tasks. It is used as a visualization tool in many applications, including remote sensing, geographic information systems and robot vision.

关键词： reconfigurable architecture stereocorrelation parallel processing multi-ring network

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parallel Approaches to Digital Signal processing Algorithms with applications in Medical imaging

Parallel Approaches to Digital Signal Processing Algorithms ...

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International conference on Signal processing and Communication Systems, ICSPCS

作者： Konstantin Kapinchev Adrian Bradu Adrian Podoleanu School of Computing School of Physical Sciences University of Kent Canterbury England Applied Optics Group School of Physical Sciences University of Kent Canterbury England

ISBN: (数字)9781728121949

ISBN: (纸本)9781728121956

关键词： Message systems Instruction sets Convolution Biomedical imaging Graphics processing units Signal processing algorithms Fourier transforms

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PC-based shared memory architecture and language

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JOURNAL OF SUPERCOMPUTING 1998年第1-2期12卷 119-136页

作者： Houzet, D Fatni, A Univ Toulouse 3 IRIT ENSEEIHT INP F-31071 Toulouse France

The Image processing applications require both computing and communication power. The object of the GFLOPS project was to study all aspects concerning the design of such computers. The project's aim was to develop a parallel architecture as well as its software environment to implement these applications efficiently. A development environment, especially a C data-parallel language, has been built for this purpose. The C// parallel language presented here, simplifies the use of such architectures by providing the programmer with a global name space and a control mechanism to exploit fine and medium grain parallelism of its applications. The main advantage of our paradigm is that it allows a unique framework to express both data and control parallelism. We have implemented this programming environment on the GFLOPS machine which supports up to 512 processor nodes, which are PC mother boards, connected over a scaleable and cost-effective network, via the PCI-bus, at a constant cost per node. The aim is to obtain at low cost a scaleable virtually shared memory machine. In this paper we discuss the design of the GFLOPS machine and its C// parallel language, and evaluate the effectiveness of the mechanisms incorporated. The analysis of the architecture's behaviour was conducted with microbenchmarks and image processing algorithms, written in C.

关键词： image processing language parallel architecture evaluation

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A Distributed Plugin Based Architecture for Medical Image processing

A Distributed Plugin Based Architecture for Medical Image Pr...

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conference on Medical imaging - Advanced PACS-Based imaging Informatics and Therapeutic applications

作者： Leon, Juan Carlos Pinzon, Alexander Sanchez, Cesar Romero, Eduardo Univ Nacl Colombia Comp Imaging & Med Applicat Lab CIM&LAB Bogota Colombia

ISBN: (纸本)9780819494481

Large volumes of data are common in medical imaging and require special applications that enable fast and reliable processing. High performance computing enables such processing by running applications in parallel. This work presents a cluster architecture for the parallel processing of DICOM datasets, where the functionality is not specified by the application itself but rather by a set of plugins. Results show that processing times reduce with each added node while network latency is kept stable.

关键词： parallel processing DICOM RMI

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parallel and Distributed Visualization The State of the Art

Parallel and Distributed Visualization The State of the Art

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5th International conference on Computer Graphics, imaging and Visualization (CGIV)

作者： Meligy, Ali Middle E Univ Grad Studies Fac Informat Technol Amman Jordan

ISBN: (纸本)9780769533599

Visualization is one of the most important applications of computer graphics. To have a parallel infrastructure for visualization, some technologies would be needed. We identify the state-of-the-art technologies that have prepared for building such an infrastructure and examine a collection of applications that would benefit from it. We consider a broad range of scientific and technological advances in visualization, which are relevant to visual supercomputing. Mainly, we present the original abstracts from the cited papers.

关键词： parallel processing distributed processing cluster computers parallel rendering algorithms visual supercomputing visualization autonomic computing mobile visualization

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