The greatest impact of the tomography technology currently occurs in medicine. The success is due to the fact that human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is a great deal of interest in using the tomography in order to know the inner part of (i) manufactured industrial objects or (ii) the machines and their means of production. In these cases, the purpose of the tomography is: (a) to control the quality of the final product and (b) to optimize the production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and it is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image may present a great spatial resolution with a satisfactory temporal resolution. Thus, the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, namely the Maximum Likelihood Estimation Method (MLEM), the Maximum Likelihood Transmitted Method (MLTR) and the Simultaneous Iterative Reconstruction Method (SIRT. The analyses involved the measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF),in order to know which algorithm fits the conditions to optimize the system better. The algorithms and the image quality analyses were performed by Matlab® 2013b.
The greatest impact of the computed tomography (CT) applications currently occurs in medicine. In industry there is much interest of using CT in order to know the interior of: (i) industrial objects; (ii) machines and their means of production. The purpose of this tomography is to: (a) control the quality of the final product and (b) optimize production and analyze the quality of the means of production. An instant non-scanning tomography system is being developed at the IPEN. This tomography comprised different collimators was simulated with Monte Carlo using the MCNP4C. The image quality was evaluated with Matlab® 2013b analyzing the contrast to noise (CNR), root mean square ratio (RMSE), signal to noise ratio (SNR) and the spatial resolution by the Modulation Transfer Function (MTF(f)), to identify which collimator fits better to the tomography in development. It was simulated three situations; (i) with no collimator; (ii) ø 25x 50 mm2 cylindrical collimator with a septum of ø5.0 x 50 mm2; (iii) ø25 x 50 mm2 cylindrical collimator with a slit septum of 24 x 5.0 x 50 mm3. RMSE values for no collimator presented better results. CNR showed that no collimator and slit collimator reaches the same CNR values, but no collimator decreases more than the slit collimator as the number of iteration rises. The hole collimator reaches a higher CNR value, however decreases more than the others. The spatial resolution with no collimator and slit collimator were around 31.9 mm, and for the hole collimator was around 20 mm
In this work the pathway of the chemical product and the kinetics parameters were evaluated in a laboratory plant settled, using 0.4 GBq (10 mL) of 67Ga citrate as radiotracer and 18 NaI(Tl) radiation detectors. The AnaComp program was used to estimate the kinetic para ameters of the acetone production. The yield of the acetone production was estimated by the percentage ratio between the areas under the curve (AUC) of the curve profiles of the final product compartment divided by the concentration found inside the chemical reactor whose result was 87% yield during the first 30 minutes of reaction.
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