Journal Article

FZJ-2019-03402

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Scatter Correction based on GPU-accelerated Full Monte Carlo Simulation for Brain PET/MRI

Ma, B. (Corresponding author)FZJ* ; Gaens, M. ; Caldeira, L.FZJ* ; Bert, J. ; Lohmann, P.FZJ* ; Tellmann, L.FZJ* ; Lerche, C.FZJ* ; Scheins, J.FZJ* ; Kops, E. R. ; Xu, H.FZJ* ; Lenz, M.FZJ* ; Pietrzyk, U. ; Shah, N. J. (Corresponding author)FZJ*

2020
IEEE New York, NY

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Please use a persistent id in citations: http://hdl.handle.net/2128/25525  doi:10.1109/TMI.2019.2921872

Abstract: 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

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Contributing Institute(s):

1. Jara-Institut Quantum Information (INM-11)
2. Physik der Medizinischen Bildgebung (INM-4)
3. JARA-BRAIN (JARA-BRAIN)

Research Program(s):

1. 573 - Neuroimaging (POF3-573) (POF3-573)

Appears in the scientific report 2020

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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