PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation

España, Samuel; Herraiz, Joaquín L.; Vicente, E.; Vaquero, J.J.; Desco, Manuel; Udías, J. M.

doi:10.1088/0031-9155/54/6/021

Cited by 75 publications

(63 citation statements)

References 34 publications

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“…The SRM was simulated with PeneloPET [9] without positron range effects but with considering all other physical effects like non colinearity or inter crystal scatter. Following a similar approach as in Ref.…”

Section: Positron Range Simulationsmentioning

confidence: 99%

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Study of CT-based positron range correction in high resolution 3D PET imaging

Cal-González

Herraiz

España

et al. 2011

Nuclear Instruments and Methods in Physics Research Section A:

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a b s t r a c tPositron range limits the spatial resolution of PET images and has a different effect for different isotopes and positron propagation materials. Therefore it is important to consider it during image reconstruction, in order to obtain optimal image quality. Positron range distributions for most common isotopes used in PET in different materials were computed using the Monte Carlo simulations with PeneloPET. The range profiles were introduced into the 3D OSEM image reconstruction software FIRST and employed to blur the image either in the forward projection or in the forward and backward projection. The blurring introduced takes into account the different materials in which the positron propagates. Information on these materials may be obtained, for instance, from a segmentation of a CT image. The results of introducing positron blurring in both forward and backward projection operations was compared to using it only during forward projection. Further, the effect of different shapes of positron range profile in the quality of the reconstructed images with positron range correction was studied. For high positron energy isotopes, the reconstructed images show significant improvement in spatial resolution when positron range is taken into account during reconstruction, compared to reconstructions without positron range modeling.

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Section: Positron Range Simulationsmentioning

confidence: 99%

“…Monte Carlo simulations may help in estimating positron range and its effect on image quality [1,3]. In a previous work [8], we simulated positron interactions and annihilation with the PeneloPET code [9].…”

Section: Introductionmentioning

confidence: 99%

Study of CT-based positron range correction in high resolution 3D PET imaging

Cal-González

Herraiz

España

et al. 2011

Nuclear Instruments and Methods in Physics Research Section A:

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“…This model was generated using the Monte Carlo code developed in our group PeneloPET [13], which is based on PENELOPE [14]. PeneloPET simulates the most relevant physical effects in a PET acquisition (positron range, non collinearity, interaction of the gamma rays with the scintillator crystals and electronics).…”

Section: System Response Matrixmentioning

confidence: 99%

Fully 3D GPU PET reconstruction

Herraiz

España

Cal-González

et al. 2011

Nuclear Instruments and Methods in Physics Research Section A:

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a b s t r a c tFully 3D iterative tomographic image reconstruction is computationally very demanding. Graphics Processing Unit (GPU) has been proposed for many years as potential accelerators in complex scientific problems, but it has not been used until the recent advances in the programmability of GPUs that the best available reconstruction codes have started to be implemented to be run on GPUs.This work presents a GPU based fully 3D PET iterative reconstruction software. This new code may reconstruct sinogram data from several commercially available PET scanners. The most important and time consuming parts of the code, the forward and backward projection operations, are based on an accurate model of the scanner obtained with the Monte Carlo code PeneloPET and they have been massively parallelized on the GPU. For the PET scanners considered, the GPU based code is more than 70 times faster than a similar code running on a single core of a fast CPU, obtaining in both cases the same images. The code has been designed to be easily adapted to reconstruct sinograms from any other PET scanner, including scanner prototypes.

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“…For this purpose, validated PET simulations tools like GATE [5] or PeneloPET [6] have been used. Another possibility to estimate the system matrix is to use real point-source measurements in combination with numérica!…”

Section: Introduction Smentioning

confidence: 99%

Projector model for efficient list-mode reconstruction in PET scanners with parallel planar detectors

Ortuño

Sportelli

Guerra

et al. 2011

2011 IEEE Nuclear Science Symposium Conference Record

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Abstrcwt-We have developed a new projector model speciflcally tailored for fast list-mode tomographic reconstructions in Positrón emission tomography (PET) scanners with parallel planar detectors. The model provides an accurate estimation of the probability distribution of coincidence events defined by pairs of scintillating crystals. This distribution is parameterized with 2D elliptical Gaussian functions defined in planes perpendicular to the main axis of the tube of response (TOR). The parameters of these Gaussian functions have been obtained by fitting Monte Cario simulations that include positrón range, acolinearity of gamma rays, as well as detector attenuation and scatter effects. The proposed model has been applied efficiently to list-mode reconstruction algorithms. Evaluation with Monte Cario simulations over a rotating high resolution PET scanner indicates that this model allows to obtain better recovery to noise ratio in OSEM (ordered-subsets, expectationmaximization) reconstruction, if compared to list-mode reconstruction with symmetric circular Gaussian TOR model, and histogram-based OSEM with precalculated system matrix using Monte Cario simulated models and symmetries.

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PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation

Cited by 75 publications

References 34 publications

Study of CT-based positron range correction in high resolution 3D PET imaging

Study of CT-based positron range correction in high resolution 3D PET imaging

Fully 3D GPU PET reconstruction

Projector model for efficient list-mode reconstruction in PET scanners with parallel planar detectors

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