ArticleIEEE transactions on medical imaging2019
DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography.
Article in IEEE transactions on medical imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
73 citing papers in PubMed, 101 citations in OpenAlex.
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- A Stability Atlas for IBSI Radiomics Features Using Synthetic Digital Phantoms, with Proof-of-Concept Physics-Based Normalisation.Journal of imaging · 2026Article
- An integrated PET/CT simulation framework for virtual imaging trials and quantitative performance evaluation.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2026Article
- Dependence of motion artifacts on the starting angle of projection data collection in a nonhelical volume scan of a 320-row CT.Physical and engineering sciences in medicine · 2026Article
- Proton therapy range uncertainty reduction using vendor-agnostic tissue characterization on a virtual photon-counting CT head scan.Medical physics · 2026Article
- Optimizing energy settings in CdTe, CZT, and Si photon-counting CT for material separation and detection.Physics in medicine and biology · 2026Article
- Precise Lung Density Quantification with a Physics-based CT Harmonizer.Radiology. Cardiothoracic imaging · 2026Observational
- Truth-based physics informed estimation of material composition in spectral CT in terms of density and effective atomic number.Physics in medicine and biology · 2026Article
- An in silico evaluation of signal and separability properties of k-edge materials in spectral CT.Scientific reports · 2026Article
- Airway quantifications of bronchitis patients with photon-counting and energy-integrating computed tomography.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Utility of the virtual imaging trials methodology for objective characterization of AI systems and training data.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Prediction of Breast Radiation Absorbed Dose Chest CT Examinations Using Machine Learning Techniques.Tomography (Ann Arbor, Mich.) · 2025Article
- Development of a customizable model for spectral photon-counting detector CT.Medical physics · 2025Article
- Sensitivity analysis of key CT simulation parameters and their impact on quality of virtual images.Medical physics · 2025Article
- Evaluation of unified harmonization of CT images across multiple tasks: A step towards AI generalizability.Medical physics · 2025Article
- An end-to-end CT simulation framework with graphical user interface and sample scanner models.Medical physics · 2025Article
- Liver fat quantification using deep silicon photon-counting CT: anRadiology advances · 2025Article
- Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.Scientific reports · 2025Article
- Simulating and correcting the pileup effect in deep-silicon photon-counting CT.Medical physics · 2025Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The purpose of this study was to develop a CT simulation platform that is: 1) compatible with voxel-based computational phantoms; 2) capable of modeling the geometry and physics of commercial CT scanners; and 3) computationally efficient. Such a simulation platform is designed to enable the virtual evaluation and optimization of CT protocols and parameters for achieving a targeted image quality while reducing radiation dose. Given a voxelized computational phantom and a parameter file describing the desired scanner and protocol, the developed platform DukeSim calculates projection images using a combination of ray-tracing and Monte Carlo techniques. DukeSim includes detailed models for the detector quantum efficiency, quantum and electronic noise, detector crosstalk, subsampling of the detector and focal spot areas, focal spot wobbling, and the bowtie filter. DukeSim was accelerated using GPU computing. The platform was validated using physical and computational versions of a phantom (Mercury phantom). Clinical and simulated CT scans of the phantom were acquired at multiple dose levels using a commercial CT scanner (Somatom Definition Flash; Siemens Healthcare). The real and simulated images were compared in terms of image contrast, noise magnitude, noise texture, and spatial resolution. The relative error between the clinical and simulated images was less than 1.4%, 0.5%, 2.6%, and 3%, for image contrast, noise magnitude, noise texture, and spatial resolution, respectively, demonstrating the high realism of DukeSim. The runtime, dependent on the imaging task and the hardware, was approximately 2-3 minutes per rotation in our study using a computer with 4 GPUs. DukeSim, when combined with realistic human phantoms, provides the necessary toolset with which to perform large-scale and realistic virtual clinical trials in a patient and scanner-specific manner.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.