1,721,119 research outputs found
Fit of EDXRF spectra with a genetic algorithm
No full textIn energy-dispersive x-ray fluorescence analysis, the estimation of the net area of the peaks is a primary requirement. This task requires a non-linear fitting of the peaks. The most common procedures are based on the Marquardt-Levenberg technique. This technique generally works well only when the spectrum is perfectly known, i.e. all the peaks are recognized. Moreover, it is sometimes difficult to introduce constraints on the fit due to peak shape or other physical properties. In this paper a new technique is proposed, based on a set of genetic operators. It works well even when the knowledge of the peaks is incomplete and it also allows one easily to introduce constraints. The results obtained with this algorithm are generally superior with respect to a standard implementation of a Marquardt-Levenberg procedure. The only drawback is the speed of convergence, that is slower than in the Marquardt-Levenberg technique
A new Monte Carlo code for simulation of the effect of irregular surfaces on X-ray spectra
No full textGenerally, quantitative X-ray fluorescence (XRF) analysis estimates the content of chemical elements in a sample based on the areas of the fluorescence peaks in the energy spectrum. Besides the concentration of the elements, the peak areas depend also on the geometrical conditions. In fact, the estimate of the peak areas is simple if the sample surface is smooth and if the spectrum shows a good statistic (large-area peaks). For this reason often the sample is prepared as a pellet. However, this approach is not always feasible, for instance when cultural heritage or valuable samples must be analyzed. In this case, the sample surface cannot be smoothed. In order to address this problem, several works have been reported in the literature, based on experimental measurements on a few sets of specific samples or on Monte Carlo simulations. The results obtained with the first approach are limited by the specific class of samples analyzed, while the second approach cannot be applied to arbitrarily irregular surfaces. The present work describes a more general analysis tool based on a new fast Monte Carlo algorithm, which is virtually able to simulate any kind of surface. At the best of our knowledge, it is the first Monte Carlo code with this option. A study of the influence of surface irregularities on the measured spectrum is performed and some results reported. © 2014 Elsevier B.V. All rights reserved
Software for x-ray fluorescence and scattering tomographic reconstruction
No full textComputer tomography is commonly based on transmitted radiation, i.e. the part of the radiation that does not interact with the sample. In recent years the scientific community has demonstrated a growing interest in alternative tomographic techniques, based on fluorescence or on scattered radiation. These kinds of tomography provide complementary information about the sample, e.g., information concerning the spatial distribution of particular elements. Furthermore, they can be applied on experimental situations where a complete turn of the apparatus around the object is not possible. However, fluorescence tomography presents certain additional difficulties in comparison to transmission tomography. This is mainly due to self-absorption effects in the sample. Few algorithms for the correction of such effects are reported in the literature. The solution proposed by Hogan et al. provides a good compromise between image quality and reconstruction speed. In this paper we report an implementation of such an algorithm and also several examples. It is our intention that this paper and the included software represent the first part of a complete set of tools for scattering and fluorescence tomography, which we intend to present in the near future
A New algorithm for computer tomographic reconstruction from partial view projections
No full textConventional algorithms for tomographic reconstruction require the acquisition of a complete set of projections at uniform angular displacements. In many cases, however, the geometry of the sample or a loss of data can significantly reduce the range of the available projections. Several algorithms have been proposed in literature to handle such situations, but their performances are low or they require strong constraints and hypothesis about the nature of the sample or the data. Here a new method is proposed. It is based on a novel morphing technique, which affords in general terms the problem of curve matching and is here specialized to the case of tomographic reconstruction. The proposed algorithm is very fast in comparison to other approaches having similar effectiveness; furthermore, it allows one to obtain good quality images even when a significant fraction of the views is absent, without any hypothesis about the nature of the sample or the kind of measurement. The results obtained by applying this technique to the Shepp–Logan phantom and to a clinical scan are reported here and discussed
Algorithmic techniques for quantitative Compton tomography
No full textCompton tomography is a non-destructive technique that allows one to reconstruct the spatial distribution of the electronic density of the sample analyzed. This information is complementary to the absorption coefficient distribution at a given energy, which can be obtained by a more conventional transmission tomography. However, the reconstruction algorithms used in Compton tomography are different and more complex than those used in transmission tomography. This is mainly due to the absorption of the X-ray photons along the path from the source to the interaction point and from the interaction point to the detector. Only a few of the reconstruction algorithms reported in the literature take absorption corrections into account, and the problems of a quantitative reconstruction have seldom been discussed. In this paper a new kind of reconstruction algorithm is described and the first results are reported and discussed
An analytical simulator for Compton tomographic measurements
No full textA critical point of several reconstruction and analysis algorithms in x-ray experiments is a fast simulation of the interaction of radiation with matter. This kind of simulations are usually based on Monte Carlo techniques, which follows each particle individual trajectory. Since the maximum number of interactions is a user-definable integer, Monte Carlo simulations allow to obtain an arbitrary precision. However, in several experiments the flux of photons that reach the detector after the interaction in the volume of interest (VOI) is very low, therefore the simulation time may be very large. Simple experiments of x-ray tomography may require several days to obtain a reasonable statistics with the faster Monte Carlo codes. Particularly, in x-y scanning tomography both the detector and the x-ray tube are highly collimated. In such cases, conventional Monte Carlo techniques are inadequate. As a possible alternative, we propose an analytical spectrum generator, which evaluates the detected signal through the differential cross-section for the single interaction with corrections for absorption of the beam (before the interaction point) and of the scattered photon (after the interaction point). It will be shown that the analytical projector proposed in this paper is several order faster than Monte Carlo based simulators. Nevertheless, the signal is evaluated with a precision that is adequate for Compton tomography and for several other experiments that involve x-ray detection. As an example a 60 per 60 pixel matrix, with a 1mm collimation of both the detector and the x-ray generator, is simulated in few minutes, while Monte Carlo based simulations cannot produce a reasonable statistics even after several days. The present work reports some of the results obtained through the analytical projector and compares them with the performances of Monte Carlo based simulations
A correction procedure for the self-absorption artifacts in X-ray Compton tomography
No full textTransmission tomography is a powerful tool in several fields of investigation, ranging from medicine to industrial quality control. It is based on the radiation that doesn't interact with the sample and that reaches the detector. However, this kind of technique cannot always be used or the information from it is poor. In some of these cases other kinds of tomography can be applied such as scattering (Compton or Rayleigh) tomography or fluorescence tomography. The use of the latter techniques requires a different reconstruction technique of that used in trasmission tomography. Some adaptation of the backprojection algorithm is often used, but in this case a complete scan of the sample is required with a fixed geometry. Another type of reconstruction algorithms are the iterative ones, but they present a high computational cost and so only small, low spatial resolution matrix, can be treated. In the past another kind of scanning technique has been proposed. It is based on two linear translations (x-y) against translation and rotation required by the backprojection algorithm. The x-y scanning presents a big advantage compared with the backprojection scanning, i.e. the reconstruction does not need to be performed on the whole sample; it can also be performed on a part of the sample, the region of interest (ROI). However this scanning technique is affected by a big drawback: the influence of X-Ray self-absortption by the matrix is stronger than the backprojection scanning producing a lower quality of the reconstruction. Several correction techniques have been described in the literature but they require an a-priori knowledge of the matrix composition or a dual-energy scanning. In this paper a recently developed technique is described. It is based only on the assumption that the Compton effect is predominant (this condition is usually found in the Compton tomography experiments described in the literature) with respect to the other interaction effect. If it is true the algorithm will be able to perfectly correct the self-absorpion effect, even when the quality of the spectra, i.e., the statistics, is poor. Some results are reported and discussed
CMOS APS detector characterization for quantitative X-ray imaging
No full textAn X-ray Imaging detector based on CMOS Active Pixel Sensor and structured scintillator is characterized for quantitative X-ray imaging in the energy range 11-30 keV. Linearity, dark noise, spatial resolution and flat-field correction are the characteristics of the detector subject of investigation. The detector response, in terms of mean Analog-to-Digital Unit and noise, is modeled as a function of the energy and intensity of the X-rays. The model is directly tested using monochromatic X-ray beams and it is also indirectly validated by means of polychromatic X-ray-tube spectra. Such a characterization is suitable for quantitative X-ray imaging and the model can be used in simulation studies that take into account the actual performance of the detector
A correction procedure for the self-absorption artifacts in X-ray Compton tomography
No full textTransmission tomography is a powerful tool in several fields of investigation, ranging from medicine to industrial quality control. It is based on the radiation that doesn't interact with the sample and that reaches the detector. However, this kind of technique cannot always be used or the information from it is poor. In some of these cases other kinds of tomography can be applied such as scattering (Compton or Rayleigh) tomography or fluorescence tomography. The use of the latter techniques requires a different reconstruction technique of that used in trasmission tomography. Some adaptation of the backprojection algorithm is often used, but in this case a complete scan of the sample is required with a fixed geometry. Another type of reconstruction algorithms are the iterative ones, but they present a high computational cost and so only small, low spatial resolution matrix, can be treated. In the past another kind of scanning technique has been proposed. It is based on two linear translations (x-y) against translation and rotation required by the backprojection algorithm. The x-y scanning presents a big advantage compared with the backprojection scanning, i.e. the reconstruction does not need to be performed on the whole sample; it can also be performed on a part of the sample, the region of interest (ROI). However this scanning technique is affected by a big drawback: the influence of X-Ray self-absortption by the matrix is stronger than the backprojection scanning producing a lower quality of the reconstruction. Several correction techniques have been described in the literature but they require an a-priori knowledge of the matrix composition or a dual-energy scanning. In this paper a recently developed technique is described. It is based only on the assumption that the Compton effect is predominant (this condition is usually found in the Compton tomography experiments described in the literature) with respect to the other interaction effect. If it is true the algorithm will be able to perfectly correct the self-absorpion effect, even when the quality of the spectra, i.e., the statistics, is poor. Some results are reported and discussed
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