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Fast GPU-based computation of the sensitivity matrix for a PET list-mode OSEM algorithm.

Moulay Ali Nassiri1, Sami Hissoiny, Jean-François Carrier

  • 1Département de radio-oncologie, Centre hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada. moulay.ali.nassiri@umontreal.ca

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Accelerated 3D list-mode OSEM PET reconstruction using GPUs significantly reduces sensitivity matrix computation time. This advancement enables faster patient-specific PET imaging for clinical use.

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Area of Science:

  • Medical Imaging
  • Computational Science
  • Nuclear Medicine

Background:

  • Graphics Processing Units (GPUs) have accelerated 3D list-mode ordered-subset expectation-maximization (LM-OSEM) for Positron Emission Tomography (PET).
  • Pre-calculated sensitivity matrices are a bottleneck, often exceeding reconstruction time.
  • This long computation time hinders routine clinical adoption of advanced PET algorithms.

Purpose of the Study:

  • To accelerate a full 3D LM-OSEM algorithm for PET reconstruction.
  • To significantly reduce the computation time of patient-specific sensitivity matrices.
  • To enable faster and more routine clinical application of advanced PET imaging.

Main Methods:

  • Implemented 3D LM-OSEM and sensitivity matrix calculations on GPUs.
  • Utilized an on-the-fly system matrix construction with multiple rays per detector pair.
  • Tested on a commercial PET system with varying voxel array sizes and resolutions.

Main Results:

  • Achieved sensitivity matrix computation times of 9s and 8s for different array sizes.
  • Demonstrated LM-OSEM reconstruction rates of 1.1 and 0.8 million events per second.
  • Significantly reduced overall reconstruction time compared to traditional methods.

Conclusions:

  • GPU acceleration of sensitivity matrix calculation is feasible and effective.
  • This approach overcomes a major obstacle for clinical implementation of list-mode PET.
  • Enables advanced PET applications like real-time dynamic studies and parametric imaging.