Acceleration of Biomedical Image Processing with Dataflow on FPGAs

Acceleration of Biomedical Image Processing with Dataflow on FPGAs

Author: Frederik Grüll

Publisher: CRC Press

Published: 2022-09-01

Total Pages: 229

ISBN-13: 1000795632

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Short compute times are crucial for timely diagnostics in biomedical applications, but lead to a high demand in computing for new and improved imaging techniques. In this book reconfigurable computing with FPGAs is discussed as an alternative to multi-core processing and graphics card accelerators. Instead of adjusting the application to the hardware, FPGAs allow the hardware to also be adjusted to the problem. Acceleration of Biomedical Image Processing with Dataflow on FPGAs covers the transformation of image processing algorithms towards a system of deep pipelines that can be executed with very high parallelism. The transformation process is discussed from initial design decisions to working implementations. Two example applications from stochastic localization microscopy and electron tomography illustrate the approach further. Topics discussed in the book include:• Reconfigurable hardware• Dataflow computing• Image processing• Application acceleration


Exploring the DataFlow Supercomputing Paradigm

Exploring the DataFlow Supercomputing Paradigm

Author: Veljko Milutinovic

Publisher: Springer

Published: 2019-05-27

Total Pages: 315

ISBN-13: 3030138038

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This useful text/reference describes the implementation of a varied selection of algorithms in the DataFlow paradigm, highlighting the exciting potential of DataFlow computing for applications in such areas as image understanding, biomedicine, physics simulation, and business. The mapping of additional algorithms onto the DataFlow architecture is also covered in the following Springer titles from the same team: DataFlow Supercomputing Essentials: Research, Development and Education, DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, and Guide to DataFlow Supercomputing. Topics and Features: introduces a novel method of graph partitioning for large graphs involving the construction of a skeleton graph; describes a cloud-supported web-based integrated development environment that can develop and run programs without DataFlow hardware owned by the user; showcases a new approach for the calculation of the extrema of functions in one dimension, by implementing the Golden Section Search algorithm; reviews algorithms for a DataFlow architecture that uses matrices and vectors as the underlying data structure; presents an algorithm for spherical code design, based on the variable repulsion force method; discusses the implementation of a face recognition application, using the DataFlow paradigm; proposes a method for region of interest-based image segmentation of mammogram images on high-performance reconfigurable DataFlow computers; surveys a diverse range of DataFlow applications in physics simulations, and investigates a DataFlow implementation of a Bitcoin mining algorithm. This unique volume will prove a valuable reference for researchers and programmers of DataFlow computing, and supercomputing in general. Graduate and advanced undergraduate students will also find that the book serves as an ideal supplementary text for courses on Data Mining, Microprocessor Systems, and VLSI Systems.


Image Processing Using FPGAs

Image Processing Using FPGAs

Author: Donald Bailey

Publisher: MDPI

Published: 2019-06-11

Total Pages: 204

ISBN-13: 303897918X

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This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs.


Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings

Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings

Author: Abdeldjalil Khelassi

Publisher: Springer Nature

Published: 2020-11-07

Total Pages: 270

ISBN-13: 3030575527

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This book collects the proceedings of the International Congress on Health Sciences and Medical Technologies (ICHSMT), held in Tlemcen, Algeria, from December 5 to 7, 2019. The proceedings present a forum for the latest projects and research in scientific and technological development with an emphasis on smart healthcare system design and future technologies. ICHSMT brings together researchers, students, and professionals from the healthcare, corporate, and academic sectors. It includes a far-reaching program supported by a variety of technical tracks that seek to promote medical technologies and innovation at a nationwide level.


Image Processing

Image Processing

Author: Yung-Sheng Chen

Publisher: IntechOpen

Published: 2009-12-01

Total Pages: 528

ISBN-13: 9789533070261

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There are six sections in this book. The first section presents basic image processing techniques, such as image acquisition, storage, retrieval, transformation, filtering, and parallel computing. Then, some applications, such as road sign recognition, air quality monitoring, remote sensed image analysis, and diagnosis of industrial parts are considered. Subsequently, the application of image processing for the special eye examination and a newly three-dimensional digital camera are introduced. On the other hand, the section of medical imaging will show the applications of nuclear imaging, ultrasound imaging, and biology. The section of neural fuzzy presents the topics of image recognition, self-learning, image restoration, as well as evolutionary. The final section will show how to implement the hardware design based on the SoC or FPGA to accelerate image processing.


Electromagnetic Imaging for a Novel Generation of Medical Devices

Electromagnetic Imaging for a Novel Generation of Medical Devices

Author: Francesca Vipiana

Publisher: Springer Nature

Published: 2023-06-29

Total Pages: 368

ISBN-13: 3031286669

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This book offers the first comprehensive coverage of microwave medical imaging, with a special focus on the development of novel devices and methods for different applications in both the diagnosis and treatment of various diseases. Upon introducing the fundamentals of electromagnetic imaging, it guides the readers to their use in practice by providing extensive information on the corresponding measurement and testing techniques. In turn, it discusses current challenges in data processing and analysis, presenting effective, novel solutions, developed by different research groups. It also describes state-of-the-art medical devices, which were designed for specific applications, such as brain stroke monitoring, lymph node diagnosis, image-guided hyperthermia, and chemotherapy response monitoring. The chapters, which report on the results of the EU-funded project EMERALD (ElectroMagnetic imaging for a novel genERation of medicAL Devices) are written by leading European engineering groups in electromagnetic medical imaging, whose coordinated action is expected to accelerate the translation of this technology “from research bench to patient bedside”. All in all, this book offers an authoritative guide to microwave imaging, with a special focus on medical imaging, for electrical and biomedical engineers, and applied physicists and mathematicians. It is also intended to inform medical doctors and imaging technicians on the state-of-the-art in non-invasive imaging technologies, at the purpose of inspiring and fostering the translation of research into clinical prototypes, by promoting a stronger collaboration between academic institutions, industrial partners, hospitals, and university medical centers.


Proceedings of the 12th International Conference on Computer Engineering and Networks

Proceedings of the 12th International Conference on Computer Engineering and Networks

Author: Qi Liu

Publisher: Springer Nature

Published: 2022-10-19

Total Pages: 1506

ISBN-13: 9811969019

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This conference proceeding is a collection of the papers accepted by the CENet2022 – the 12th International Conference on Computer Engineering and Networks held on November 4-7, 2022 in Haikou, China. The topics focus but are not limited to Internet of Things and Smart Systems, Artificial Intelligence and Applications, Communication System Detection, Analysis and Application, and Medical Engineering and Information Systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings. This will enable them to produce, maintain, and manage systems with high levels of trustworthiness and complexity.


Design for Embedded Image Processing on FPGAs

Design for Embedded Image Processing on FPGAs

Author: Donald G. Bailey

Publisher: John Wiley & Sons

Published: 2011-06-13

Total Pages: 503

ISBN-13: 0470828528

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Dr Donald Bailey starts with introductory material considering the problem of embedded image processing, and how some of the issues may be solved using parallel hardware solutions. Field programmable gate arrays (FPGAs) are introduced as a technology that provides flexible, fine-grained hardware that can readily exploit parallelism within many image processing algorithms. A brief review of FPGA programming languages provides the link between a software mindset normally associated with image processing algorithms, and the hardware mindset required for efficient utilization of a parallel hardware design. The design process for implementing an image processing algorithm on an FPGA is compared with that for a conventional software implementation, with the key differences highlighted. Particular attention is given to the techniques for mapping an algorithm onto an FPGA implementation, considering timing, memory bandwidth and resource constraints, and efficient hardware computational techniques. Extensive coverage is given of a range of low and intermediate level image processing operations, discussing efficient implementations and how these may vary according to the application. The techniques are illustrated with several example applications or case studies from projects or applications he has been involved with. Issues such as interfacing between the FPGA and peripheral devices are covered briefly, as is designing the system in such a way that it can be more readily debugged and tuned. Provides a bridge between algorithms and hardware Demonstrates how to avoid many of the potential pitfalls Offers practical recommendations and solutions Illustrates several real-world applications and case studies Allows those with software backgrounds to understand efficient hardware implementation Design for Embedded Image Processing on FPGAs is ideal for researchers and engineers in the vision or image processing industry, who are looking at smart sensors, machine vision, and robotic vision, as well as FPGA developers and application engineers. The book can also be used by graduate students studying imaging systems, computer engineering, digital design, circuit design, or computer science. It can also be used as supplementary text for courses in advanced digital design, algorithm and hardware implementation, and digital signal processing and applications. Companion website for the book: www.wiley.com/go/bailey/fpga


Accelerating Reverse Engineering Image Processing Using FPGA

Accelerating Reverse Engineering Image Processing Using FPGA

Author: Matthew Joshua Harris

Publisher:

Published: 2019

Total Pages: 62

ISBN-13:

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In recent decades, field programmable gate arrays (FPGAs) have evolved beyond simple, expensive computational components with minimal computing power to complex, inexpensive computational engines. Today, FPGAs can perform algorithmically complex problems with improved performance compared to sequential CPUs by taking advantage of parallelization. This concept can be readily applied to the computationally dense field of image manipulation and analysis. Processed on a standard CPU, image manipulation suffers with large image sets processed by highly sequential algorithms, but by carefully adhering to data dependencies, parallelized FPGA functions or kernels offer the possibility of significant improvement through threaded CPU functions. This thesis will examine the possibilities of moving a program featuring several image manipulation and analysis operations to a hardware/software build on a modern FPGA. The paper will focus on the implementation and performance improvements of the proposed method as well as the results of moving portions of the program to FPGA hardware.