A GPU-cloud based Monte Carlo simulation platform for National Particle Therapy Research Center
A GPU-cloud based Monte Carlo simulation platform for National Particle Therapy Research Center
批准号:
9150784
负责人:
Steve Bin Jiang
金额:
$20.77万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
已结题
起止时间:
至 2018-01-31
关键词:
AddressAnatomyAreaCarbonClinicalCloud ComputingCodeCommunitiesConflict (Psychology)DatabasesDevelopmentDoseEnsureGeometryGoalsHourImageryInternetLanguageMeasurementMicroscopicMissionModelingMonte Carlo MethodNaturePhysicsPilot ProjectsPlayProcessRadiation therapyRadiobiologyResearchResearch ActivityResearch PersonnelResourcesRoleRunningSamplingServicesStagingStructureSystemSystems DevelopmentTechniquesTechnologyTest ResultTestingTherapeutic StudiesTimeUncertaintyValidationbasecloud basedflexibilityhandheld mobile deviceinteractive toollaptopnovelparticleparticle beamparticle physicsparticle therapyphysical processprototypesimulationstatisticssuccesstherapy designtooltreatment planningusabilityuser-friendlyvirtualweb interface
中文摘要
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英文摘要
Project Summary
Monte Carlo (MC) simulation is a valuable tool for radiation therapy. Particularly for particle beam radiation
therapy (PBRT), its remarkable value has been well recognized. Examples include, but not limited to,
accurately calculating dose distributions that are highly sensitive to treatment geometry and anatomy, reducing
range uncertainty, developing novel treatment verification techniques, capturing radiobiological effects from the
microscopic level, and designing treatment facility. Hence, researchers are eager to have a fast, robust, and
easy-to-use MC system in their studies. Yet, there are two main difficulties to use current available MC
packages for PBRT, namely low computational efficiency and highly required user expertise. The conflicts
between the great desire of using MC and the difficulties of using it have impeded research and clinical
activities in PBRT to significantly. As part of the planning process for National Particle Therapy Research
Center (NPTRC), we propose in this pilot project a highly accurate, efficient, yet user-friendly centralized MC
simulation system using novel graphics-processing unit (GPU) and cloud-computing technologies. Different
from conventional MC packages running on the user's end, our system remotely resides in a cloud inside
NPTRC and provides MC simulation services to PBRT researchers though standard web browsers. While our
long-term goal is to deliver novel MC simulations to facilitate the establishments of NPTRC and its future
research activities, as well as to service the entire PBRT community, the goal of this pilot project is to initiate
efforts toward the long-term goal by developing and validating a prototype system focusing on particle beam
dose calculations to demonstrate feasibility and impacts. The deliverability of this project has been clearly
demonstrated by mature technologies and our extensive preliminary studies. The strong research team,
particularly the integration of Dr. Parodi for particle physics modeling, also ensures success. Our goal will be
accomplished by pursuing two specific aims (SAs): (1) System developments: develop web interface, physics
database, and core GPU-based MC simulation codes. (2) System validations: Comprehensively validate the
computational accuracy of our system and test its efficiency. Perform end-to-end functionality test in a
representative research scenario. This pilot project fits into the overall plan for the proposed NPTRC facility. (1)
Being an integral component of NPTRC, it will play a critical role for the planning stage by offering virtual yet
realistic simulations of different clinical, physical, and technical scenarios. In the long run, our system will
greatly expand NPTRC's research capacity and hence significantly contribute to the establishments of its
leading role in PBRT field. (2) Our system service PBRT field with high quality MC simulations. Continuous
developments will add much more features to address needs from different research aspects. This is aligned
with the NPTRC's mission of providing resources for researchers to investigate important problems in PBRT.
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Artificial Intelligence-Based Quality Assurance for Online Adaptive Radiotherapy
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批准号:10589063
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资助金额:$53.91万
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财政年份:2022
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负责人:Steve Bin Jiang
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依托单位:
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财政年份:2015
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依托单位:
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依托单位:
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批准号:8619515
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资助金额:$28.04万
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财政年份:2011
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负责人:Steve Bin Jiang
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依托单位:
Low dose cone beam CT for image guided adaptive radiotherapy
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批准号:8264781
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项目类别:
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资助金额:$29.32万
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财政年份:2011
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依托单位:
Low dose cone beam CT for image guided adaptive radiotherapy
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批准号:8026135
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资助金额:$29.56万
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财政年份:2011
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依托单位:
Low dose cone beam CT for image guided adaptive radiotherapy
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批准号:8444698
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项目类别:
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资助金额:$27.34万
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财政年份:2011
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负责人:Steve Bin Jiang
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依托单位:
A Tumor Tracking System for Image Guided Radiotherapy
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批准号:6985219
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项目类别:
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资助金额:$26.07万
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财政年份:2005
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负责人:Steve Bin Jiang
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依托单位:
A Tumor Tracking System for Image Guided Radiotherapy
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批准号:7140120
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项目类别:
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资助金额:$11.13万
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财政年份:2005
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负责人:Steve Bin Jiang
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依托单位:
A Tumor Tracking System for Image Guided Radiotherapy
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批准号:7555283
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项目类别:
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财政年份:2005
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负责人:Steve Bin Jiang
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依托单位:
海外基金