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Optimal conditions for X-ray imaging by mathematical simulation
Linköping University, Department of Mechanical Engineering, Engineering Materials. Linköping University, The Institute of Technology.
Linköping University, Department of Mechanical Engineering, Engineering Materials. Linköping University, The Institute of Technology.
1999 (English)In: AIP Conference Proceedings 509 / [ed] Sarah Kallsen, Connie Nessa, Donald O. Thompson, Dale E. Chimenti, Linda Poore, 1999, 665-672 p.Conference paper, Published paper (Refereed)
Abstract [en]

Image quality strongly affects the detectability, which is the possibility to detect defects. To obtain maximum detectability it is necessary to conduct the testing with optimal equipment settings. In radiography and computerized tomography based on conventional poly-energetic x-rays, the optimal equipment settings depend on the imaging task. An imaging task is defined as testing of a specific object with a specific defect, defined by composition and geometry. However, the optimal equipment settings (e.g., x-ray tube potential, x-ray filtration and exposure time) are tedious to find experimentally. This is particularly true for industrial applications due to the wide range of imaging tasks. In this work, mathematical models of the image collection process for radiography and computerized tomography have been developed. The objective has been to develop techniques to aid the imaging operator to find optimal imaging parameters. With the models it is possible to find the optimal settings and to predict the detectability of defects in terms of its size as a function of imaged object diameter and these are formulated in terms of detectable detail—object diameter diagram. It is shown that the image quality is very sensitive with respect to the settings, with e.g., slightly non-optimal choice of x-ray filter thickness leading to a loss of image quality that cannot be compensated by varying the x-ray tube potential. Furthermore, non-optimal conditions are found to considerably reduce the detectability of defects, especially for large objects.

Place, publisher, year, edition, pages
1999. 665-672 p.
Keyword [en]
nondestructive testing, X-ray imaging, radiography, computerised tomography, modelling, digital simulation, optical transfer function, optimisation, random noise, image processing
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-30136DOI: 10.1063/1.1306113Local ID: 15616ISBN: 1-56396-930-0 (print)OAI: oai:DiVA.org:liu-30136DiVA: diva2:250957
Conference
Review of progress in quantative nondestructive evaluation, 25-30 July, Montreal, Canada
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-02-14
In thesis
1. Optimised performance of industrial high resolution computerised tomography
Open this publication in new window or tab >>Optimised performance of industrial high resolution computerised tomography
2000 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The purpose of non-descructive enluation (NDE) is to acquire knowledge of the investigated sample. Digital x-ray imaging techniques such as radiography or computerised tomography (CI) produce images of the interior of a sample. The obtained image quality determines the possibility of detecting sample, ·elated features, e.g. details and flaws. this thesis presents a method of optinllsing the performance of industrial X-ray equipment for the imaging task at issue in order to obtain images with high quality.

CT produces maps of the X-ray linear attenuation of the sample's interior. CT can produce two-dimensional cross-section images or three-dimensional images with volumetric information on the investigated sample. The image contrast and noise depend on both the investig-Ated sample and the equipment and settings used (X-ray tube potential, X-ray filtration, exposure time, etc.). Hence, it is vital to find the optimal equipment settings in order to obtain images of high quality.

To be able to mathematically optimise the image guality, it is necessary to have a model of the X-ray imaging system together with an appropriate measure of image quality. The optimisation is performed with a developed model for an X-ray image-intensifier-based radiography system. The model predicts the mean value and variance of the measured signal level in the collected radiographic images. The traditionally used measure of physical image guality is the signal-to-noise ratio (SNR). To calculate the signal-to-noise ratio, a well-defined detail (flaw) is required. It was found that maximising the SNR leads to ambiguities, the optimised settings found by maximising the SNR were dependent on the material in the detail. When CT is performed on irregular shaped samples containing density and compositional variations, it is difficult to define which SNR to use for optimisation. This difficulty is solved by the measures of physical image quality proposed here, the ratios geometry-sensitivity/ noise, density-sensitivity/noise, and mass attenuation-sensitivity/noise. With these measures, a meiliod is presented that finds the optimal eguipment settings, where no improvement can be made without worsening at least one other sensitivity/noise ratio.

This thesis includes modelling and verification of the sharpness of the CT system in terms of the modulation transfer function, MTF. Together with the limiting perception factor and the maximised SNR, the detectability limits for any specific contrasting detail in the centre of a cylindrical sample can be determined. It is also demonstrated that the model can be used to suppress beam hardening when collecting CT-data. When homogeneous samples are imaged, the model can in addition be used to make post-processing corrections for suppressing the beam hardening artefacts.

Wavelet-based local tomography has been found to produce images with good accuracy from projection data only from a small region in a sample. Tlus technique is demonstrated on thermal barrier coatings, which contain internal cracks. With optimised eguipment settings and geometrical magnification of a region in the sample, wavelet-based local tomography produced high-resolution images of excellent quality. The increased resolution reveals features in the microstructure that cannot be resolved wiili traditional CT. This technigue will be a useful tool for characterisation of the microstructure in advanced materials.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2000. 34 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 659
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-30060 (URN)15520 (Local ID)91-7219-887-7 (ISBN)15520 (Archive number)15520 (OAI)
Public defence
2000-12-05, Sal C3, Linköpings universitet, Linköping, 10:15 (Swedish)
Opponent
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-02-14

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