Experimental analysis of high-speed gamma-ray tomography performance

Abstract

High-speed gamma-ray tomography (HSGT) based on multiple fan-beam collimated radioisotope sources has proved to be an efficient and fast method for cross sectional imaging of the dynamics in different industrial processes. The objective of the tomography system described here is to identify the flow regime of gas/liquid pipe flows. The performance of such systems is characterized by the spatial resolution, the speed of response and the measurement resolution of the attenuation coefficient. The work presented here is an experimental analysis of how the measurement geometry and the reconstruction method affect the error of the reconstructed pixel values. These relationships are well established for medical x-ray tomography where high intensity x-ray tubes are used as sources. For radioisotope sources, however, the radiation intensity is limited, which causes the measurement uncertainty, i.e. the Poisson noise, to be considerably higher. In addition, the influence of scattered radiation is more severe in a multiple source radioisotope system compared to that of x-ray systems. A computer-controlled flexible geometry gamma-ray tomograph has been developed to acquire experimental data for different fan-beam measurement geometries, and these data have subsequently been used for image reconstruction using seven different iterative image reconstruction algorithms. The results show that the reconstruction algorithms perform cross sectional images with different quality and that there is virtually nothing to be gained by using more than seven sources for flow regime classification of multiphase pipe flow consisting of gas, oil and water.

Concentration and Temperature Tomography at Elevated Pressures

“…Once this is completed for each pixel in the measurement region, the solution is presented as a pair of temperature and concentration images. The quality of these reconstructions is quantified using the root mean-squared-error (RMSE) [32]:…”

Process tomography and estimation of velocity fields

“…The working principle of g-ray CT is similar to X-ray CT with the difference that the X-ray tube is replaced by an isotopic g-ray source. Systems of this type have been developed and applied by several groups, see for example, Kumar, Moslemian, and Dudukovic (1995), Al-Dahhan et al (2007), Hampel et al (2007), Bieberle, Hoppe, Schleicher, and Hampel (2011), Bieberle, Schleicher, and Hampel (2007), Johansen, Hjertaker, Froystein, and Olsen (1996), Johansen, Hampel, and Hjertaker (2010, and Maad and Johansen (2008). The actual velocity field estimation in X-ray and g-ray imaging modalities is done indirectly by analysing a sequence of images with, for example, cross-correlation techniques explained above.…”

Dynamic characterization of a high speed gamma-ray tomograph

“…It can be shown that this expression has a minimum when the product µr equals 2 [16]. Using data from associated the plot in [17] it is shown that the optimal path length Table 1 Tomograms reconstructed from polypropylene phantom, using the ILST algorithm with eight iterations on a 32 × 32 grid for different sensor data integration times and variable rotational speed. The RMSE is calculated for each image.…”