Scatter Correction Based on GPU-Accelerated Full Monte Carlo Simulation for Brain PET/MRI
| Autor: | Hancong Xu, Julian Bert, Christoph Lerche, Philipp Lohmann, Liliana Caldeira, Nadim Jon Shah, Elena Rota Kops, Michaela Gaens, Mirjam Lenz, Lutz Tellmann, B. H. Ma, Jürgen Scheins, Uwe Pietrzyk |
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| Rok vydání: | 2019 |
| Předmět: |
Speedup
Computer science Monte Carlo method Graphics processing unit Imaging phantom 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Imaging Three-Dimensional Robustness (computer science) Humans Electrical and Electronic Engineering Radiological and Ultrasound Technology Brain Neoplasms Phantoms Imaging Detector Brain Equipment Design Magnetic Resonance Imaging Computer Science Applications Positron-Emission Tomography Tomography ddc:620 Algorithm Monte Carlo Method Software Algorithms |
| Zdroj: | IEEE transactions on medical imaging 39(1), 140-151 (2020). doi:10.1109/TMI.2019.2921872 |
| ISSN: | 1558-254X |
| DOI: | 10.1109/TMI.2019.2921872 |
| Popis: | Accurate scatter correction is essential for qualitative and quantitative PET imaging. Until now, scatter correction based on Monte Carlo simulation (MCS) has been recognized as the most accurate method of scatter correction for PET. However, the major disadvantage of MCS is its long computational time, which makes it unfeasible for clinical usage. Meanwhile, single scatter simulation (SSS) is the most widely used method for scatter correction. Nevertheless, SSS has the disadvantage of limited robustness for dynamic measurements and for the measurement of large objects. In this work, a newly developed implementation of MCS using graphics processing unit (GPU) acceleration is employed, allowing full MCS-based scatter correction in clinical 3D brain PET imaging. Starting from the generation of annihilation photons to their detection in the simulated PET scanner, all relevant physical interactions and transport phenomena of the photons were simulated on GPUs. This resulted in an expected distribution of scattered events, which was subsequently used to correct the measured emission data. The accuracy of the approach was validated with simulations using GATE (Geant4 Application for Tomography Emission), and its performance was compared to SSS. The comparison of the computation time between a GPU and a single-threaded CPU showed an acceleration factor of 776 for a voxelized brain phantom study. The speedup of the MCS implemented on the GPU represents a major step toward the application of the more accurate MCS-based scatter correction for PET imaging in clinical routine. |
| Databáze: | OpenAIRE |
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