Scatter correction techniques in 3D PET: a Monte Carlo evaluation

Castiglioni, Isabella; Cremonesi, O.; Gilardi, Maria Carla; Bettinardi, Valentino; Rizzo, Giovanna; Savi, A.; Bellotti, E.; Fazio, Ferruccio

doi:10.1109/23.819282

Cited by 55 publications

(21 citation statements)

References 11 publications

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“…Dedicated particle transport tools have been developed specifically for the simulation of PET or SPECT devices. An early tool PET-EGS [124] used EGS, with GEANT4 used in the leading tool, GATE [125], and in GAMOS [126], and Penelope in PeneloPET [127].…”

Section: Medical Imagingmentioning

confidence: 99%

Detector Simulation

Apostolakis

2020

Particle Physics Reference Library

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This chapter provides an overview of particle and radiation transport simulation, as it is used in the simulation of detectors in High Energy and Nuclear Physics (HENP) experiments and, briefly, in other application areas. The past decade has seen significant growth in the availability of large networked computing power and particle transport tools with increasing precision available to HENP experiments, and enabled the use of detailed simulation at an unprecedented scale. After describing the uses of detector simulation and giving an overview of its components, we will examine selected cases and key uses of detector simulation in experiments and its impact. 11.1 Overview of Detector Simulation 11.1.1 Uses of Detector Simulation Simulating the generation of particles in an initial collision, the interaction of these primaries and their daughter particles with the material of a detector and the response of the detector is a key element of recent experiments. Its importance has grown with each generation of experiments from LEP, B-factories, and the Tevatron, through to the current generation at the LHC, due to the increased precision requirements. It will be a significant element in planned experiments at superB factories, the International Linear Collider (ILC), the Future Circular Collider (FCC), and also for numerous ongoing and smaller future experiments.

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Section: Medical Imagingmentioning

confidence: 99%

Detector Simulation

Apostolakis

2020

Particle Physics Reference Library

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“…The MC simulations were performed by the MC software package PET-EGS [17]. The PET-EGS input data: 1) a description of radioactive sources (both analytical and digital phantoms), in terms of radioactivity and media distribution and 2) a description of the PET scanner, in terms of physical and geometrical characteristics.…”

Section: A MC Simulationsmentioning

confidence: 99%

A Monte Carlo model of noise components in 3D PET

Castiglioni

Cremonesi

Gilardi

et al. 2002

IEEE Trans. Nucl. Sci.

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This work presents a new model, developed by Monte Carlo methods, to estimate noise components (scatter and random coincidences) in three-dimensional (3-D) positron emission tomography (PET). The model allows the amount, spatial, and temporal distribution of true, scattered, and random coincidences to be estimated independently for any radioactive source (both phantoms and real patients), taking proper account of system dead time. The model was applied to a 3-D NaI(Tl) current-generation PET scanner for which there are no currently available methods for estimating scatter and random components in whole-body studies. The quantitative accuracy of the developed noise model was tested by comparing simulated and measured PET data in terms of physical parameters, count-rate curves, and spatial distribution profiles. Scatter and random components were assessed for phantoms representing brain, abdomen, and whole-body studies. Evidence was found of high scatter and random contribution in 3-D PET clinical studies. The clinical response of the PET system, in terms of signal-to-noise ratio, was assessed and optimized, confirming the suitability of the default energy window, although suggesting a possible improvement by setting a lower energy threshold higher than the current default. The proposed noise model applies to any current generation 3-D PET scanner and has been included in the Monte Carlo software package PET-EGS, devoted to 3-D PET and freely available from the authors.Index Terms-Monte Carlo methods, noise, positron emission tomography (PET).

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“…MC simulation calculates the migration of photons by considering multiple scattering events. However, MC simulation is computationally very demanding for a 3D PET (Castiglioni et al 1999). Hence, Watson et al (1996) developed what they termed the single scatter simulation (SSS) algorithm.…”

Section: Introductionmentioning

confidence: 99%

Fully 3D iterative scatter-corrected OSEM for HRRT PET using a GPU

Kim

Ye²

2011

Phys. Med. Biol.

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Accurate scatter correction is especially important for high-resolution 3D positron emission tomographies (PETs) such as high-resolution research tomograph (HRRT) due to large scatter fraction in the data. To address this problem, a fully 3D iterative scatter-corrected ordered subset expectation maximization (OSEM) in which a 3D single scatter simulation (SSS) is alternatively performed with a 3D OSEM reconstruction was recently proposed. However, due to the computational complexity of both SSS and OSEM algorithms for a high-resolution 3D PET, it has not been widely used in practice. The main objective of this paper is, therefore, to accelerate the fully 3D iterative scatter-corrected OSEM using a graphics processing unit (GPU) and verify its performance for an HRRT. We show that to exploit the massive thread structures of the GPU, several algorithmic modifications are necessary. For SSS implementation, a sinogram-driven approach is found to be more appropriate compared to a detector-driven approach, as fast linear interpolation can be performed in the sinogram domain through the use of texture memory. Furthermore, a pixel-driven backprojector and a ray-driven projector can be significantly accelerated by assigning threads to voxels and sinograms, respectively. Using Nvidia's GPU and compute unified device architecture (CUDA), the execution time of a SSS is less than 6 s, a single iteration of OSEM with 16 subsets takes 16 s, and a single iteration of the fully 3D scatter-corrected OSEM composed of a SSS and six iterations of OSEM takes under 105 s for the HRRT geometry, which corresponds to acceleration factors of 125× and 141× for OSEM and SSS, respectively. The fully 3D iterative scatter-corrected OSEM algorithm is validated in simulations using Geant4 application for tomographic emission and in actual experiments using an HRRT.

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Scatter correction techniques in 3D PET: a Monte Carlo evaluation

Cited by 55 publications

References 11 publications

Detector Simulation

Detector Simulation

A Monte Carlo model of noise components in 3D PET

Fully 3D iterative scatter-corrected OSEM for HRRT PET using a GPU

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