ArticleEJNMMI physics2018
SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool.
Article in EJNMMI physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Noise-aware system generative model (NASGM): positron emission tomography (PET) image simulation framework with observer validation studies.Medical physics · 2025Article
- On the implementation of acollinearity in PET Monte Carlo simulations.Physics in medicine and biology · 2024Article
- FAST (fast analytical simulator of tracer)-PET: an accurate and efficient PET analytical simulation tool.Physics in medicine and biology · 2024Article
- Validation of a discovery MI 4-ring model according to the NEMA NU 2-2018 standards: from Monte Carlo simulations to clinical-like reconstructions.EJNMMI physics · 2024Article
- An automatic pipeline for PET/MRI attenuation correction validation in the brain.EJNMMI physics · 2023Article
- Investigation and optimization of PET-guided SPECT reconstructions for improved radionuclide therapy dosimetry estimates.Frontiers in nuclear medicine · 2023Article
- Evaluation of a method based on synthetic data inserted into raw data prior to reconstruction for the assessment of PET scanners.EJNMMI physics · 2022Article
- Improved 3D tumour definition and quantification of uptake in simulated lung tumours using deep learning.Physics in medicine and biology · 2022Article
- 3D Convolutional Neural Network-Based Denoising of Low-Count Whole-BodyDiagnostics (Basel, Switzerland) · 2022Article
- Evaluation of attenuation correction in PET/MRI with synthetic lesion insertion.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation forMedical physics · 2021Article
- Monte Carlo simulation of digital photon counting PET.EJNMMI physics · 2020Article
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Authors and funding
5 authors.
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Abstract
backgroundPositron-emission tomography (PET) simulators are frequently used for development and performance evaluation of segmentation methods or quantitative uptake metrics. To date, most PET simulation tools are based on Monte Carlo simulations, which are computationally demanding. Other analytical simulation tools lack the implementation of time of flight (TOF) or resolution modelling (RM). In this study, a fast and easy-to-use PET simulation-reconstruction package, SiMulAtion and ReconsTruction (SMART)-PET, is developed and validated, which includes both TOF and RM. SMART-PET, its documentation and instructions to calibrate the tool to a specific PET/CT system are available on Zenodo. SMART-PET allows the fast generation of 3D PET images. As input, it requires one image representing the activity distribution and one representing the corresponding CT image/attenuation map. It allows the user to adjust different parameters, such as reconstruction settings (TOF/RM), noise level or scan duration. Furthermore, a random spatial shift can be included, representing patient repositioning. To evaluate the tool, simulated images were compared with real scan data of the NEMA NU 2 image quality phantom. The scan was acquired as a 60-min list-mode scan and reconstructed with and without TOF and/or RM. For every reconstruction setting, ten statistically equivalent images, representing 30, 60, 120 and 300 s scan duration, were generated. Simulated and real-scan data were compared regarding coefficient of variation in the phantom background and activity recovery coefficients (RCs) of the spheres. Furthermore, standard deviation images of each of the ten statistically equivalent images were compared.
resultsSMART-PET produces images comparable to actual phantom data. The image characteristics of simulated and real PET images varied in similar ways as function of reconstruction protocols and noise levels. The change in image noise with variation of simulated TOF settings followed the theoretically expected behaviour. RC as function of sphere size agreed within 0.3-11% between simulated and actual phantom data.
conclusionsSMART-PET allows for rapid and easy simulation of PET data. The user can change various acquisition and reconstruction settings (including RM and TOF) and noise levels. The images obtained show similar image characteristics as those seen in actual phantom data.
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