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Fully-3D GPU PET reconstruction

J. L. Herrai, S. Espana, J. Cal-Gonzalez, J. J. Vaquero, M. Desco, J. M. Udias
Grupo de Fisica Nuclear, Dpto. Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid, Spain
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (16 December 2010)

@article{Herrai2010,

   title={“Fully-3DGPUPETreconstruction”},

   journal={“NuclearInstrumentsandMethodsinPhysicsResearchSectionA:Accelerators},

   volume={“InPress},

   number={“”},

   pages={“-“},

   year={“2010”},

   note={“”},

   issn={“0168-9002”},

   doi={“DOI:10.1016/j.nima.2010.12.043”},

   url={“http://www.sciencedirect.com/science/article/B6TJM-51R0707-7/2/264fd88548cf3f9f39b10668c1dacb8b”},

   author={“J.L.HerraiandS.EspanaandJ.Cal-GonzalezandJ.J.VaqueroandM.DescoandJ.M.Udias”},

   keywords={“Graphicsprocessingunit”}

}

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Fully-3D iterative tomographic image reconstruction is computationally very demanding. Graphics Processing Unit (GPU) have been proposed for many years as potentially accelerators in complex scientific problems, but it has not been until the recent advances in the programmability of GPUs that the best available reconstruction codes have started to be implemented to be run on GPUs. This work presents a GPU-based fully-3D PET iterative reconstruction software. This new code may reconstruct sinogram data from several commercially available PET scanners. The most important and time-consuming parts of the code, the forward and backward projection operations, are based on an accurate model of the scanner obtained with the Monte Carlo code PeneloPET and they have been massively parallelized on the GPU. For the PET scanners considered, the GPU-based code is more than 70 times faster than a similar code running on a single core of a fast CPU, obtaining in both cases the same images. The code has been designed to be easily adapted to reconstruct sinograms from any other PET scanner, including scanner prototypes.
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