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Advanced Monte Carlo simulations of emission tomography imaging systems with GATE.

David SarrutMateusz BałaManuel BardièsJulien BertMaxime ChauvinKonstantinos P ChatzipapasMathieu DupontAne EtxebesteLouise M FanchonSébastien JanGunjan KayalAssen S KirovPaweł KowalskiWojciech KrzemienJoey LabourMirjam LenzGeorge LoudosBrahim MehadjiLaurent MénardChristian MorelPanagiotis PapadimitroulasMagdalena RafecasJulien SalvadoriDaniel SeiterMariele StockhoffEtienne TestaCarlotta TrigilaUwe PietrzykStefaan VandenbergheMarc-Antoine VerdierDimitris VisvikisKarl ZiemonsMilan ZvolskýEmilie Roncali
Published in: Physics in medicine and biology (2021)
Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.
Keyphrases
  • monte carlo
  • high resolution
  • artificial intelligence
  • machine learning
  • big data
  • magnetic resonance imaging
  • deep learning
  • molecular dynamics
  • magnetic resonance
  • mass spectrometry
  • computed tomography
  • image quality