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The last 25 years have seen an explosion in the number of new x-ray based imaging methods and applications. In reviewing these new capabilities we see that the ability to generate improved data quality underlies a number of the major advances. Improvement in the quality of x-ray sources, in detector resolution and dynamic range, in data analysis methods both in image processing and in reconstruction techniques have yielded significant advances in image quality. In addition to the improved imaging hardware, the use of computers play a key role in extending capabilities in high speed computed tomography, in real time image enhancement, in automated defect recognition and in the development of accurate x-ray inspection simulations. The ability to generate information and to analyze the complexities introduced by typical inspection demands can quickly outstrip even today's computational resources. Developments in parallel computing and computer memory are beginning to managing the huge data volumes now routinely produced and open up a number of new applications. Some examples include high-resolution 3D-image generation with the capability to probe micron length scales, dual energy computed tomography providing improved airport security, materials characterization techniques providing new tool for process development, and x-ray image formation modeling. The ability to model the details of the generation of bremsstrahlung radiation and its interaction with the complex geometry of the object under consideration provide for the first time a means to determine and quantify the optimal parameters for an inspection. These advances over the last 25 years represent exciting time in x-ray imaging, the impact of which will be played out in the next decade. ©2001 American Institute of Physics.
Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images but does not image object structures itself. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of the N-Particle Monte Carlo code MCNP is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). Additionally it opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper intends to discuss the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. It is important to note that the use of Monte Carlo methods is a laboratory type of technique for basic investigations because of the enormous computing power that is needed. For in-field applications such as for inspection planing simplified models are of much greater importance and increasingly in use. ©2003 American Institute of Physics
The paper presents a special reconstruction algorithm that is capable to monitor density differences in multi-phase flows. The flow cross section is represented as discrete dynamic random field. A fixed gray value is assigned to each flow phase characterizing the material property of the phase. The image model is given by a set of non-linear stochastic difference equations. The corresponding inversion task is not accessible by common tomographic techniques applying reconstruction algorithms like filtered backprojection or algebraic reconstruction technique (ART). The developed algorithm is based on the Kalman filter technique adapted to non-linear phenomena. The average velocity distribution together with the corresponding covariance matrix of the liquid flow through a pipe serves as prior information in statistical sense. To overcome the non-linearity in the process model as well as in the measurement model the statistical linearization technique is applied. Moreover the Riccati equation, giving the error covariance matrix, and the equation for the optimal gain coefficients can be solved in advance and later used in the filter equation. It turns out that the resulting reconstruction or filter algorithm is recursive, i.e. yielding the quasi-optimal solution to the formulated inverse problem at every reconstruction step by successively counting for the new information collected in the projections. The applicability of the developed algorithm is discussed in terms of characterizing or monitoring a multi-phase flow in a pipe. ©2003 American Institute of Physics
Determining scatter ratios at high energies (> ~ 1MeV) presents challenges not immediately obvious from measurements at conventional X-ray energies. This includes reduced attenuation even in heavy elements as well as a stronger forward bias of scattering. In order to check the reliability of different measurement setups with regard to material thicknesses, distances, and collimation, attenuation and scattering were separately simulated using a Monte Carlo model. The simulation results help in understanding the sources of radiation scattered into the detection area, thereby aiding in eliminating undesired contributions.
Within the framework of the European project PICASSO, the radiographic simulator aRTist (analytical Radiographic Testing inspection simulation tool) developed by BAM has been extended for reliability assessment of film and digital radiography. NDT of safety relevant components of aerospace industry requires the proof of probability of detection (POD) of the inspection. Modeling tools can reduce the expense of such extended, time consuming NDT trials, if the result of simulation fits to the experiment. Our analytic simulation tool consists of three modules for the description of the radiation source, the interaction of radiation with test pieces and flaws, and the detection process with special focus on film and digital industrial radiography. It features high processing speed with near–interactive frame rates and a high level of realism. A concept has been developed as well as a software extension for reliability investigations, completed by a user interface for planning automatic simulations with varying parameters and defects. Furthermore, an automatic image analysis procedure is included to evaluate the defect visibility. The radiographic modeling from 3D CAD of aero engine components and quality test samples are compared as a precondition for real trials. This enables the evaluation and optimization of film replacement for application of modern digital equipment for economical NDT and defined POD.
X-ray compton tomography
(2014)
The potentials of incoherent X-ray Scattering (Compton) tomography are investigated. Imaging materials of very different density or atomic number at once is a perpetual challenge for X-ray tomography or radiography, in general. In a basic laboratory set-up for simultaneous perpendicular Compton Scattering and direct beam attenuation tomographic scans are conducted by single channel photon counting. This results in asymmetric distortions of the projection profiles of the scattering CT-data set. ln a first approach corrections of Compton scattering data by taking advantage of rotational symmetry yield tomograms without major geometric artefacts.
A cylindrical sample composed of PE, PA, PVC, glass and wood demonstrates similar Compton contrast for all the substances, while the conventional absorption tomogram only reveals the two high order materials.
Compärison to neutron tomography reveals astonishing similarities except for the glass component (without hydrogen). Therefore, Compton CT bears the potential to replace neutron tomography, which requires much more efforts.
The new standard ISO 176362:2013 'NDT of welds: Radiographic testing - Part 2: X- and gamma ray techniques with digital detectors' describes a complex procedure for film replacement by phosphor imaging plates and digital detector arrays. RT modeling software should consider these detector types, X-ray film, and the standard requirements for image quality. Practitioners expect the same visibility of image quality indicators (IQI) in the simulated radiographs as in the experimental exposures. The proposed benchmark test is based on the comparison of experimental radiographs taken at BAM with modeled ones of participants. The experimental setup and the determination of the equivalent penetrameter sensitivity (EPS) as described in the procedure of ASTM E 746 are used for quantitative evaluation of the achievable contrast sensitivity for step hole IQIs as considered in Annex B of ISO 17636-2. System classification data for Computed Radiography (CR) and film systems will be provided by BAM according to ISO 116991 for selected film systems and according to ASTM E 2446 for selected CR systems. The classification of films and digital detectors is based on the measurement of the dose response function, the basic spatial resolution (SRb) of the image, and the measured image noise, which depends on the detector efficiency, the quantum statistics, and the detector fixed pattern noise.
As a matter of fact, avoiding unexpected events with an undesired outcome is an element of survival strategies.
Such events are encountered unexpectedly mainly because they occur rarely. Both, safety and security measures are the main pillars to prevent them by appropriate inspections. Common tools in both areas e.g. are radiological technologies enabling an insight into objects to detect suspicious features without even touching them. Since any of these measures is linked to efforts, costs or even obstructions of ongoing processes, it needs a rationale to invest into an appropriate activity. A putative objection to take action in this direction always could be the question 'when and how often it could happen'. This gave rise to find approaches how to define 'rare events' and how to deal with them. Since they entail both, the frequency of occurrence and the unpleasantness of the possible outcome make them to have something in common with the definition of risk: a combination of the probability of occurrence of harm and the severity of that harm. Tackling putative consequences is one side of the coin whereas understanding the rareness of an event is the other, an aspect that worries but not always fully understood.
As a first step in approaching the subject 'rare events', the putative occurrence rate is considered in terms of probability distribution functions or their cumulative ones, resp. The problems of estimating an incidence of such an event will be tackled subsequently with the problem of assessing the reliability of diagnostic measures.
Any numeric approach of dealing with rare events inevitably remains an ill defined or 'ill-posed' problem that needs additional information for a reasonably satisfying solution. Ways to ease this situation can be found in utilizing additional information, also commonly called prior knowledge, that might be introduced via the Bayesian inference or by regularization algorithms. Simplified models will demonstrate how to apply such tools.
As a consequence, there are ways helping to avoid unexpected ad 'surprises' by taking adequate measures in due time upon the correct perception of certain indications.
Correctly modeling the continuous photon spectrum of X-ray tubes requires detailed knowledge of the probability distribution of electron properties at the time of X-ray photon creation, in particular electron energy, depth within the target, and direction of movement. Semi-analytical X-ray spectrum models frequently assume a very simplified or even uniform distribution of electron direction. In the case of thick targets and small deviations from normal incidence this is a useful approximation. For thin targets or large deviations from normal incidence the correct distribution of electron directions becomes more important. As calculation speed is an important aspect of semi-analytical models compared to Monte Carlo simulations, fast evaluation of the distribution of electron properties is highly desirable. The approach presented here numerically evaluates the evolution of a discrete probability distribution of electron properties due to single electron scatter interactions within a plane target. This allows capturing the important aspects of the electron distribution while achieving runtimes of a few seconds up to a minute on a standard office PC.
Radiography benchmark 2014
(2015)
The purpose of the 2014 WFNDEC RT benchmark study was to compare predictions of various models of radiographic techniques, in particular those that predict the contribution of scattered radiation. All calculations were carried out for homogenous materials and a mono-energetic X-ray point source in the energy range between 100 keV and 10 MeV. The calculations were to include the best physics approach available considering electron binding effects. Secondary effects like X-ray fluorescence and bremsstrahlung production were to be taken into account if possible. The problem to be considered had two parts. Part I examined the spectrum and the spatial distribution of radiation behind a single iron plate. Part II considered two equally sized plates, made of iron and aluminum respectively, only evaluating the spatial distribution. Here we present the results of above benchmark study, comparing them to MCNP as the assumed reference model. The possible origins of the observed deviations are discussed.
A special slit collimator was developed earlier for fast acquisition of X-ray back scatter images. The design was based on a twisted slit design (ruled surfaces) in a Tungsten block to acquire backscatter images. The comparison with alternative techniques as flying spot and coded aperture pin hole technique could not prove the expected higher contrast sensitivity. In analogy to the coded aperture technique, a novel multi slit camera was designed and tested. Several twisted slits were parallelly arranged in a metal block. The CAD design of different multi-slit cameras was evaluated and optimized by the computer simulation packages aRTist and McRay. The camera projects a set of equal images, one per slit, to the digital detector array, which are overlaying each other. Afterwards, the aperture is corrected based on a deconvolution algorithm to focus the overlaying projections into a single representation of the object. Furthermore, a correction of the geometrical distortions due to the slit geometry is performed. The expected increase of the contrast-to-noise ratio is proportional to the square root of the number of parallel slits in the camera. However, additional noise has to be considered originating from the deconvolution operation. The slit design, functional principle, and the expected limits of this technique are discussed.