GPU-accelerated Monte Carlo simulation of MV-CBCT Article Swipe
Mengying Shi
,
Marios Myronakis
,
Matthew W. Jacobson
,
D. Ferguson
,
Christopher Williams
,
Mathias Lehmann
,
Paul Baturin
,
Pascal Huber
,
Rony Fueglistaller
,
Ingrid Valencia Lozano
,
Thomas C. Harris
,
Daniel Morf
,
Ross Berbeco
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6560/abaeba
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6560/abaeba
Monte Carlo simulation (MCS) is one of the most accurate computation methods for dose calculation and image formation in radiation therapy. However, the high computational complexity and long execution time of MCS limits its broad use. In this paper, we present a novel strategy to accelerate MCS using a graphic processing unit (GPU), and we demonstrate the application in mega-voltage (MV) cone-beam computed tomography (CBCT) simulation. A new framework that generates a series of MV projections from a single simulation run is designed specifically for MV-CBCT acquisition. A Geant4-based GPU code for photon simulation is incorporated into the framework for the simulation of photon transport through a phantom volume. The FastEPID method, which accelerates the simulation of MV images, is modified and integrated into the framework. The proposed GPU-based simulation strategy was tested for its accuracy and efficiency in a Catphan 604 phantom and an anthropomorphic pelvis phantom with beam energies at 2.5 MV, 6 MV, and 6 MV FFF. In all cases, the proposed GPU-based simulation demonstrated great simulation accuracy and excellent agreement with measurement and CPU-based simulation in terms of reconstructed image qualities. The MV-CBCT simulation was accelerated by factors of roughly 900–2300 using an NVIDIA Tesla V100 GPU card against a 2.5 GHz AMD Opteron™ Processor 6380.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1361-6560/abaeba
- OA Status
- green
- Cited By
- 9
- References
- 56
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3048382340
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3048382340Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1361-6560/abaebaDigital Object Identifier
- Title
-
GPU-accelerated Monte Carlo simulation of MV-CBCTWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
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2020-08-12Full publication date if available
- Authors
-
Mengying Shi, Marios Myronakis, Matthew W. Jacobson, D. Ferguson, Christopher Williams, Mathias Lehmann, Paul Baturin, Pascal Huber, Rony Fueglistaller, Ingrid Valencia Lozano, Thomas C. Harris, Daniel Morf, Ross BerbecoList of authors in order
- Landing page
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https://doi.org/10.1088/1361-6560/abaebaPublisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.ncbi.nlm.nih.gov/pmc/articles/9100851Direct OA link when available
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Monte Carlo method, Computer science, Computer graphics (images), Computational science, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
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9Total citation count in OpenAlex
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2025: 2, 2024: 4, 2023: 1, 2022: 1, 2021: 1Per-year citation counts (last 5 years)
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56Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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