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Monte-Carlo simulations are used in many applications, among which radiotherapy and nuclear medicine imaging. Different codes can be used in these contexts, most of them coming from the branch of particle physics. Gate is currently one of the most popular code for Monte Carlo simulations in nuclear medicine, as it is flexible, simple, and gives accurate results.
Gate has been developed since 2001 by a consortium of international labs without any specific financial support, and has been publicly released in 2004. Regular releases have enhanced Gate features. However, Gate Monte-Carlo simulations requires intensive computation. The fGate project has already contributed to accelerate the code. However, Gate is still not efficient enough to run a radiotherapy simulation for a clinical application.
The new hGate project (hybrid architectures for Gate simulations) aims at solving the computation problem of Gate by using Graphical Processor Units (GPU). The CPU/GPU architecture was chosen because of its low cost in comparison to classical CPU clusters. In radiotherapy applications, the hGate project might make it possible to run Gate Monte-Carlo simulations compatible with the time constraints of these applications.
The hGate project is supported by a French grant ANR-09-COSI-004. The main steps of the project are summarized below:
T1 - Portage feasibility on GPU
T1.1 - Code profiling and timing of Gate/Geant4,
December 2010 to May 2010
T1.2 - Portage evaluation on GPU, June 2010 to November 2010
T2 - hGate development
T2.1 - Coding hGate on CPU/GPU, December 2010 to November 2011
T2.2 - Strategy to use a CPU/GPU cluster, March 2010 to November 2011
T2.3 - Performance evaluation, September 2011 to March 2012
T3 - Applications and testing
T3.1 - Radiotherapy application, January 2012 to November 2012
T3.2 - Iterative reconstruction in medical imaging, May 2012 to November 2012
T3.3 - 3D optical pre-clinical imaging simulation, May 2012 to November 2012
Bert J, Perez-Ponce H, El Bitar Z, Jan S, Boursier Y, Vintache D, Bonissent A, Morel C, Brasse D & Visvikis D, "Geant4-based Monte Carlo simulations on GPU for medical applications", Physics in Medicine and Biology, 2013, 58, 5593-5611.
Perez-Ponce H, Bitar Z E, Boursier Y, Vintache D, Bonissent A, Morel C, Brasse D, Visvikis D & Bert J, "Implementing Geant4 on GPU for medical applications", IEEE Nuclear Science Symposium and Medical Imaging Conference, 2011, 2703-2707, ieeexplore
Bert J, Perez-Ponce H, Jan S, El Bitar Z, Gueth P, Cuplov V, Chekatt H, Benoit D, Sarrut D, Boursier Y, Brasse D, Buvat I, Morel C & Visvikis D, "Hybrid GATE: A GPU/CPU implementation for imaging and therapy applications", IEEE Nuclear Science Symposium and Medical Imaging Conference, 2012.
Cuplov V, Buvat I, Mesradi M, Pain F & Jan S, "Optical imaging simulation using GATE", IEEE Nuclear Science Symposium and Medical Imaging Conference, 2012.