Graphics Processing Unit Based High Performance Computing In Radiation Therapy
DOWNLOAD
Download Graphics Processing Unit Based High Performance Computing In Radiation Therapy PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Graphics Processing Unit Based High Performance Computing In Radiation Therapy book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Graphics Processing Unit Based High Performance Computing In Radiation Therapy
DOWNLOAD
Author : Xun Jia
language : en
Publisher: CRC Press
Release Date : 2018-09-21
Graphics Processing Unit Based High Performance Computing In Radiation Therapy written by Xun Jia and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-21 with Medical categories.
Use the GPU Successfully in Your Radiotherapy Practice With its high processing power, cost-effectiveness, and easy deployment, access, and maintenance, the graphics processing unit (GPU) has increasingly been used to tackle problems in the medical physics field, ranging from computed tomography reconstruction to Monte Carlo radiation transport simulation. Graphics Processing Unit-Based High Performance Computing in Radiation Therapy collects state-of-the-art research on GPU computing and its applications to medical physics problems in radiation therapy. Tackle Problems in Medical Imaging and Radiotherapy The book first offers an introduction to the GPU technology and its current applications in radiotherapy. Most of the remaining chapters discuss a specific application of a GPU in a key radiotherapy problem. These chapters summarize advances and present technical details and insightful discussions on the use of GPU in addressing the problems. The book also examines two real systems developed with GPU as a core component to accomplish important clinical tasks in modern radiotherapy. Translate Research Developments to Clinical Practice Written by a team of international experts in radiation oncology, biomedical imaging, computing, and physics, this book gets clinical and research physicists, graduate students, and other scientists up to date on the latest in GPU computing for radiotherapy. It encourages you to bring this novel technology to routine clinical radiotherapy practice.
Accelerating Radiation Dose Calculation With High Performance Computing And Machine Learning For Large Scale Radiotherapy Treatment Planning
DOWNLOAD
Author : Ryan Neph
language : en
Publisher:
Release Date : 2020
Accelerating Radiation Dose Calculation With High Performance Computing And Machine Learning For Large Scale Radiotherapy Treatment Planning written by Ryan Neph and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Radiation therapy is powered by modern techniques in precise planning and execution of radiation delivery, which are being rapidly improved to maximize its benefit to cancer patients. In the last decade, radiotherapy experienced the introduction of advanced methods for automatic beam orientation optimization, real-time tumor tracking, daily plan adaptation, and many others, which improve the radiation delivery precision, planning ease and reproducibility, and treatment efficacy. However, such advanced paradigms necessitate the calculation of orders of magnitude more causal dose deposition data, increasing the time requirement of all pre-planning dose calculation. Principles of high-performance computing and machine learning were applied to address the insufficient speeds of widely-used dose calculation algorithms to facilitate translation of these advanced treatment paradigms into clinical practice. To accelerate CT-guided X-ray therapies, Collapsed-Cone Convolution-Superposition (CCCS), a state-of-the-art analytical dose calculation algorithm, was accelerated through its novel implementation on highly parallelized GPUs. This context-based GPU-CCCS approach takes advantage of X-ray dose deposition compactness to parallelize calculation across hundreds of beamlets, reducing hardware-specific overheads, and enabling acceleration by two to three orders of magnitude compared to existing GPU-based beamlet-by-beamlet approaches. Near-linear increases in acceleration are achieved with a distributed, multi-GPU implementation of context-based GPU-CCCS. Dose calculation for MR-guided treatment is complicated by electron return effects (EREs), exhibited by ionizing electrons in the strong magnetic field of the MRI scanner. EREs necessitate the use of much slower Monte Carlo (MC) dose calculation, limiting the clinical application of advanced treatment paradigms due to time restrictions. An automatically distributed framework for very-large-scale MC dose calculation was developed, granting linear scaling of dose calculation speed with the number of utilized computational cores. It was then harnessed to efficiently generate a large dataset of paired high- and low-noise MC doses in a 1.5 tesla magnetic field, which were used to train a novel deep convolutional neural network (CNN), DeepMC, to predict low-noise dose from faster high-noise MC- simulation. DeepMC enables 38-fold acceleration of MR-guided X-ray beamlet dose calculation, while remaining synergistic with existing MC acceleration techniques to achieve multiplicative speed improvements. This work redefines the expectation of X-ray dose calculation speed, making it possible to apply new highly-beneficial treatment paradigms to standard clinical practice for the first time.
Image Based Computer Assisted Radiation Therapy
DOWNLOAD
Author : Hidetaka Arimura
language : en
Publisher: Springer
Release Date : 2017-01-26
Image Based Computer Assisted Radiation Therapy written by Hidetaka Arimura and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-26 with Medical categories.
This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in computer-assisted radiation therapy based on image engineering. It also traces major technical advancements and research findings in the field of image-based computer-assisted radiation therapy. In high-precision radiation therapies, novel approaches in image engineering including computer graphics, image processing, pattern recognition, and computational anatomy play important roles in improving the accuracy of radiation therapy and assisting decision making by radiation oncology professionals, such as radiation oncologists, radiation technologists, and medical physicists, in each phase of radiation therapy. All the topics presented in this book broaden understanding of the modern medical technologies and systems for image-based computer-assisted radiation therapy. Therefore this volume will greatly benefit not only radiation oncologists and radiologists but also radiation technologists, professors in medical physics or engineering, and engineers involved in the development of products to utilize this advanced therapy.
High Performance Computing For The Optimization Of Radiation Therapy Treatment Plans
DOWNLOAD
Author : Felix Liu
language : en
Publisher:
Release Date : 2024
High Performance Computing For The Optimization Of Radiation Therapy Treatment Plans written by Felix Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
High Performance Graphics Processor Based Computed Tomography Reconstruction Algorithms For Nuclear And Other Large Scale Applications
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2013
High Performance Graphics Processor Based Computed Tomography Reconstruction Algorithms For Nuclear And Other Large Scale Applications written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S & T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.
A Gpu Based Implementation For Improved Online Rebinning Performance In Clinical 3 D Pet
DOWNLOAD
Author : Dilip Reddy Patlolla
language : en
Publisher:
Release Date : 2009
A Gpu Based Implementation For Improved Online Rebinning Performance In Clinical 3 D Pet written by Dilip Reddy Patlolla and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Online rebinning is an important and well-established technique for reducing the time required to process Positron Emission Tomography data. However, the need for efficient data processing in a clinical setting is growing rapidly and is beginning to exceed the capability of traditional online processing methods. High-count rate applications such as Rubidium 3-D PET studies can easily saturate current online rebinning technology. Real-time processing at these high-count rates is essential to avoid significant data loss. In addition, the emergence of time-of-flight (TOF) scanners is producing very large data sets for processing. TOF applications require efficient online Rebinning methods so as to maintain high patient throughput. Currently, new hardware architectures such as Graphics Processing Units (GPUs) are available to speedup data parallel and number crunching algorithms. In comparison to the usual parallel systems, such as multiprocessor or clustered machines, GPU hardware can be much faster and above all, it is significantly cheaper. The GPUs have been primarily delivered for graphics for video games but are now being used for High Performance computing across many domains. The goal of this thesis is to investigate the suitability of the GPU for PET rebinning algorithms.
Strategies For Adaptive Radiation Therapy
DOWNLOAD
Author : Junyi Xia
language : en
Publisher:
Release Date : 2009
Strategies For Adaptive Radiation Therapy written by Junyi Xia and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
ABSTRACT: Image guided radiation therapy (IGRT) requires developing advanced methods for target localization. Once target motion is identified, the patient specific treatment margin can be incorporated into the treatment planning, accurately delivering the radiation dose to the target and minimizing the dose to the normal tissues. Deformable image registration (DIR) has become an indispensable tool to analyze target motion and measure physiological change by temporal imaging or time series volumetric imaging, such as four-dimensional computed tomography (4DCT). Current DIR algorithms suffer from inverse inconsistency, where the deformation mapping is not unique after switching the order of the images. Moreover, long computation time of current DIR implementation limits its clinical application to offline analysis. This dissertation makes several major contributions: First, an inverse consistent constraint (ICC) is proposed to constrain the uniqueness of the correspondence between image pairs. The proposed ICC has the advantage of 1) improving registration accuracy and robustness, 2) not requiring explicitly computing the inverse of the deformation field, and 3) reducing the inverse consistency error (ICE). Moreover, a variational registration model, based on the maximum likelihood estimation, is proposed to accelerate the algorithm convergence and allow for inexact image pixel matching within an optimized variation for noisy image pairs.
Computational And Physical Quality Assurance Tools For Radiotherapy
DOWNLOAD
Author : Yan Jiang Graves
language : en
Publisher:
Release Date : 2013
Computational And Physical Quality Assurance Tools For Radiotherapy written by Yan Jiang Graves and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Radiation therapy aims at delivering a prescribed amount of radiation dose to cancerous targets while sparing dose to normal organs. Treatment planning and delivery in modern radiotherapy are highly complex. To ensure the accuracy of the delivered dose to a patient, a quality assurance (QA) procedure is needed before the actual treatment delivery. This dissertation aims at developing computational and physical tools to facilitate the QA process. In Chapter 2, we have developed a fast and accurate computational QA tool using a graphics processing unit based Monte Carlo (MC) dose engine. This QA tool aims at identifying any errors in the treatment planning stage and machine delivery process by comparing three dose distributions: planned dose computed by a treatment planning system, planned dose and delivered dose reconstructed using the MC method. Within this tool, several modules have been built. (1) A denoising algorithm to smooth the MC calculated dose. We have also investigated the effects of statistical uncertainty in MC simulations on a commonly used dose comparison metric. (2) A linear accelerator source model with a semi-automatic commissioning process. (3) A fluence generation module. With all these modules, a web application for this QA tool with a user friendly interface has been developed to provide users with easy access to our tool, facilitating its clinical utilizations. Even after an initial treatment plan fulfills the QA requirements, a patient may experience inter-fractional anatomy variations, which compromise the initial plan optimality. To resolve this issue, adaptive radiotherapy (ART) has been proposed, where treatment plan is redesigned based on most recent patient anatomy. In Chapter 3, we have constructed a physical deformable head and neck (HN) phantom with in-vivo dosimetry capability. This phantom resembles HN patient geometry and simulates tumor shrinkage with a high level of realism. The ground truth deformation field can be measured from built-in surface markers, which is then used to verify the accuracy of an important ART step of deformable image registration. Our experiments also demonstrate the feasibility of using this phantom as an end-to-end ART QA phantom with an emphasis on testing the dose deliver accuracy.
Peterson S Graduate Programs In Engineering And Applied Sciences 1996
DOWNLOAD
Author : Peterson's Guides
language : en
Publisher: Peterson Nelnet Company
Release Date : 1995-12-10
Peterson S Graduate Programs In Engineering And Applied Sciences 1996 written by Peterson's Guides and has been published by Peterson Nelnet Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-12-10 with Reference categories.
Graduate students depend on this series and ask for it by name. Why? For over 30 years, it's been the only one-stop source that supplies all of their information needs. The new editions of this six-volume set contain the most comprehensive information available on more than 1,500 colleges offering over 31,000 master's, doctoral, and professional-degree programs in more than 350 disciplines.New for 1997 -- Non-degree-granting research centers, institutes, and training programs that are part of a graduate degree program.Five discipline-specific volumes detail entrance and program requirements, deadlines, costs, contacts, and special options, such as distance learning, for each program, if available. Each Guide features "The Graduate Adviser", which discusses entrance exams, financial aid, accreditation, and more.Interest in these fields has never been higher! And this is the source to the 3,400 programs currently available -- from bioengineering and computer science to construction management.
Adaptive Radiation Therapy
DOWNLOAD
Author : X. Allen Li
language : en
Publisher: CRC Press
Release Date : 2011-01-27
Adaptive Radiation Therapy written by X. Allen Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-27 with Medical categories.
Modern medical imaging and radiation therapy technologies are so complex and computer driven that it is difficult for physicians and technologists to know exactly what is happening at the point-of-care. Medical physicists responsible for filling this gap in knowledge must stay abreast of the latest advances at the intersection of medical imaging an