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The project series CTSimU was initiated with the goal to develop a set of procedures to enable the determination of the task-specific measurement uncertainty of a CT system numerically by radiographic simulation. The first project (2019-2022) “Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation - CTSimU” was focused on the sufficient physical correctness of the radiographic simulation and created as a result a test framework for simulation softwares and a draft of a VDI standard in the series VDI/VDE 2630 for this application. However, for the realistic simulation of a CT system in a simulation software (i.e. a digital twin), not only the correctness of the simulation software itself is crucial, but also the quality of the parameterization of the CT system in the simulation software - this represents the starting point of the 2nd project “Realistic Simulation of real CT systems with a basic-qualified Simulation Software - CTSimU2” (2022-2024).
The parameterization of a CT system in a simulation software can be divided into four steps: after the data acquisition at the real CT system (step 1) follows the evaluation of the acquired data for the generation of general parameter specifications (step 2). It follows the transfer of the parameters into the specific simulation software (step 3) and the validation of the resulting simulation parameters by a suitable test (step 4). The intended result of the project CTSimU2 is a draft VDI standard (for VDI/VDE 2630) for this test, which contains an informative annex on the state of the art regarding the possibilities for parameter determination.
Virtual CT with aRTist
(2021)
Simulation becomes more and more important in modern CT imaging. It is increasingly used to optimize techniques for complex applications, to support the preparation of written procedures, and for educational purposes. The radiographic simulator aRTist is a modelling tool which simulates X-ray imaging using a hybrid analytical and Monte Carlo method to efficiently model the radiation transport. In addition to the relevant physical effects such as absorption, scattering and fluorescence, simplified fast models are employed to describe the characteristics of the X-ray source and the detector. aRTist is well equipped to model realistic X-ray imaging setups due to the ability to load exported CAD object descriptions. A simple CT scan module is contained in aRTist which allows the simulation of standard (circular cone beam) scanning trajectories.
This training session starts with a general introduction to aRTist and will highlight its basic usage. Furthermore, the focus is on the configuration of scan trajectories and batch simulations for virtual CT. The aim is to enable the audience to use the aRTist software for their own experiments in virtual CT.
AdvanCT Virtual CT
(2021)
Simulation becomes more and more important in modern CT imaging. It is increasingly used to optimize techniques for complex applications, and for educational purposes. Simulation can also be used for uncertainty estimation of dimensional CT measurements. The radiographic simulator aRTist is a modelling tool which simulates X-ray imaging using a hybrid analytical and Monte-Carlo method to efficiently model the radiation transport. In addition to the relevant physical effects such as absorption and scattering, simplified fast models are employed to describe the characteristics of the X-ray source and the detector. aRTist is well equipped to model realistic X-ray imaging setups due to the ability to load exported CAD object descriptions. By repetitive simulation runs aRTist can function as virtual CT device. A simple CT scan module is contained in aRTist which allows the simulation of standard (circular cone beam) scanning trajectories.
AdvanCT is a module for aRTist which allows to set up more complex scanning trajectories by attaching geometrical modification functions to the objects in the radiographic scene. In this way, advanced scanning modes can be realized. In addition to deterministic motion, also random variations can be introduced. By combining random variations with deterministic motion, non-ideal (realistic) CT scan geometries can be simulated, e.g. focal spot drift and mechanical instability of the axis of rotation. The AdvanCT module conveniently allows to construct these scenarios in a graphical interface and provides a preview before starting the (potentially long running) batch job. Therefore, deviations from ideal CT scan trajectories can be easily adjusted which is a necessary step towards uncertainty determination from simulation.
The simulator aRTist combines analytical and Monte Carlo methods to efficiently model the radiographic process of industrial radiology. In this contribution we focus on virtual computer tomography, the simulation of tomographic scans. The possibilities to simulate complex scanning trajectories are shown in combination with the tomographic reconstruction using individual projection matrices.
Virtual CT acquisition and reconstruction of complex and noisy scanning trajectories in aRTist
(2019)
In modern CT imaging, simulation has become an important tool to minimize cost- and time-intensive measurements. It is increasingly used to optimize techniques for complex applications, to support the preparation of written procedures, and for educational purposes. We extended the CT simulation software ‘aRTist’ with a module to set-up arbitrary trajectories including disturbing influences during the scan. Moreover, such geometric deviations can be compensated by the internal reconstruction tool.
Industrial radiography or Radiographic Testing (RT) is a method of non-destructive testing where many types of manufactured components can be examined to verify the internal structure and integrity of the specimen. The computer program aRTist can generate synthetic radiographs from a virtual RT test set-up. In the field of industrial radiology simulation is used, e.g. to optimize techniques for complex applications, to support the preparation of written procedures, and for education purposes.
The simulator aRTist combines analytical and Monte Carlo methods to efficiently model the radiation transport. The program comes with a graphical user interface written in Tcl/Tk. In combination of Tcl/Tk and the 3D capabilities of the visualization toolkit (VTK) a practical and convenient simulator has been realized. This will be illustrated by discussing application scenarios of classical radiography, X-ray computer tomography, and X-ray backscatter imaging. Additionally, some insight to the software implementation of the simulator will be given.
Modelling becomes more and more important in modern NDE. It is increasingly used to optimize techniques for complex applications, to support the preparation of written procedures, and for education purposes. To describe the complete chain of RT, the model includes simulating all necessary properties of X- or Gamma-ray sources, the interaction of photons with material with special attention to scattered radiation, the detection process, and the complete geometrical RT setup handling arbitrary parts or constructions. Depending on the given inspection problem and the influencing factors that should be addressed by the simulation, an appropriate physical model has to be chosen to describe the underlying interaction mechanisms. The simulator aRTist combines analytical and Monte Carlo methods to efficiently model the radiation transport such that transmission as well as scatter techniques can be modelled. In this contribution we focus on Monte Carlo simulation of scatter contribution within aRTist. Examples for RT/tomographic applications and back-scatter techniques are presented to demonstrate the usability of the presented simulation tool for a broad range of radiological applications.
A model is presented that employs a unified approach for
simulating the photon energy spectra for transmission and direct
beam targets composed of arbitrary homogeneous materials. In order
to achieve this, a detailed model of electron transport within the
target is employed. The validity of the developed model is shown
through comparisons with Monte Carlo simulations as well as
measurements for a number of different configurations.