2013
DOI: 10.1088/0031-9155/58/16/5593
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Geant4-based Monte Carlo simulations on GPU for medical applications

Abstract: Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MC… Show more

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Cited by 74 publications
(69 citation statements)
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References 26 publications
(34 reference statements)
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“…Last, an ongoing project deals with the implementation of dedicated GPU codes for gamma camera acquisitions in order to speed up Monte Carlo image simulation procedure. 25 Thanks to the modular nature of TestDose, further developments may also consider PET imaging integration. The TestDose software will also serve the community for any research projects requiring the generation of scintigraphic images or dosimetry computation from an anthropomorphic model with a specific biodistribution.…”
Section: Resultsmentioning
confidence: 99%
“…Last, an ongoing project deals with the implementation of dedicated GPU codes for gamma camera acquisitions in order to speed up Monte Carlo image simulation procedure. 25 Thanks to the modular nature of TestDose, further developments may also consider PET imaging integration. The TestDose software will also serve the community for any research projects requiring the generation of scintigraphic images or dosimetry computation from an anthropomorphic model with a specific biodistribution.…”
Section: Resultsmentioning
confidence: 99%
“…Finally, in terms of computational time the current performance of the GaTE MCs platform is not compatible with a potential clinical use, even if one considers the use of pre-operative CT imaging and subsequent treatment planning. However, the necessary computational times are expected to be dramatically reduced in the future by using hybrid computing architectures, such as graphical card units (GPUs), including recently proposed implementations for Geant4 based MCss both in imaging and radiotherapy applications [23][24][25].…”
Section: Discussionmentioning
confidence: 99%
“…Modeling of X-ray photon propagation is complex and not often possible ton achieve analytically. To visualize the amount of radiation dosage during surgery, we consider Monte Carlo (MC) simulations, which are algorithmic methods that approximate radiation exposure by simulating the X-ray imaging process, and tracking the resulting scattered particles towards clinicians and patients during surgery (20,21). Optimizing the position of any C-arm device (to minimize radiation exposure) is challenging since the context, the imaging parameters, and the patient's and staff's positioning need to be considered in the MC simulations.…”
Section: Interventional 3d Augmented Reality In Orthopedic Trauma Anmentioning
confidence: 99%