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gPET: a GPU-based, accurate and efficient Monte Carlo simulation tool for PET.

Youfang Lai1, Yuncheng Zhong2,3, Ananta Chalise1

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|November 12, 2019
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gPET, a graphics processing unit (GPU)-based Monte Carlo (MC) simulation tool, significantly accelerates Positron Emission Tomography (PET) system development. This accurate and efficient tool achieves a 500x speedup over traditional methods.

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Area of Science:

  • Medical Imaging Physics
  • Computational Science
  • Nuclear Engineering

Background:

  • Monte Carlo (MC) simulations are crucial for Positron Emission Tomography (PET) system development.
  • Existing MC simulation packages often have long execution times, hindering practical PET simulations.

Purpose of the Study:

  • To develop and validate gPET, a graphics processing unit (GPU)-accelerated MC simulation tool for PET.
  • To address the computational time limitations of current PET simulation software.

Main Methods:

  • gPET utilizes the NVidia CUDA platform for GPU parallel processing.
  • The simulation is modularized into source management, gamma transport, and detector signal processing.
  • A hybrid geometry approach combines voxelized phantoms and parametrized detectors.

Main Results:

  • gPET demonstrated high accuracy, with differences below 3.18% (energy) and 2.54% (crystal index) compared to GATE.
  • Achieved a significant speedup factor of 500x on a single GPU over a multi-core CPU implementation.
  • Validated across functional modules, physics models, and complex detector geometries.

Conclusions:

  • gPET is an accurate and highly efficient MC simulation tool for PET.
  • The GPU-based approach substantially reduces simulation time for PET systems.
  • Enables more flexible and rapid examination of PET system designs and parameters.