Comparison of surface-based and image-based quality metrics for the analysis of dimensional computed tomography data

Arenhart, Francisco A.; Nardelli, Vitor C.; Donatelli, Gustavo Daniel

doi:10.1016/j.csndt.2016.05.002

Cited by 10 publications

(3 citation statements)

References 12 publications

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“…Assessing the resolution by means of the edge spread function does not allow to evaluate resolution along the entire measurement chainand does not directly address the problem of assessing the resolution of the extracted surface. , However, only a small number of methods has been presented in the literature about assessing resolution after the surface determination stage [21][22][23] and resolution in the volumetric dataset already provides some indication of what resolution will be in the final surface. When assessing the resolution in the volumetric dataset using the edge spread function, the reconstruction using detector binning showed the worst resolution out of all test cases, followed by the cases based on 628 projections (the least number of projections) as expected.…”

Section: Discussionmentioning

confidence: 99%

Sinogram interpolation to decrease acquisition time in X-ray computed tomography measurement of surface topography

Körner¹,

Lawes²,

Newton³

et al. 2019

eJNDT

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The effects of reducing the number of projections and using sinogram interpolation in X-ray computed tomography measurement were evaluated by considering the quality of volumetric reconstruction and extracted surface topographies. Using a test sample, the number of projections acquired was reduced in steps of 20% from the theoretical reference value. The obtained data sets were upsampled by sinogram interpolation. The quality of the volumetric reconstructions was assessed by introducing dedicated measures of noise and resolution. The surface topographies extracted from the data sets were evaluated using statistical topography models. It was shown that sinogram interpolation can be used as a tool to reduce the number of projections and still obtain sufficient quality surface topographies.

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Section: Discussionmentioning

confidence: 99%

Sinogram interpolation to decrease acquisition time in X-ray computed tomography measurement of surface topography

Körner¹,

Lawes²,

Newton³

et al. 2019

eJNDT

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“…Later, Arenhart et al [9] presented a multi-wave standard designed for evaluating the frequency response in extracting surfaces with CT systems and its use to evaluate some factors influencing the structural resolution of CT-based measurements. The use of the multi-wave standard was then extended in order to perform a comparative analysis on the use of image-based and surfacebased metrics to assess the quality of CT-based dimensional data [10].…”

Section: Outcomes Of Bilateral Research Projectsmentioning

confidence: 99%

CT-based dimensional metrology developments in Brazil: Current status and outlook

Baldo¹,

Fernandes²

2023

eJNDT

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Since the 1980s Computed Tomography (CT) has been used in many industrial sectors for non-destructive inspection, including flaw detection, failure analysis, and assembly analysis. Back to the 2000s CT has become a metrology tool for dimensioning and tolerancing analysis as well, in which some topics have gained attention of researchers, such as the traceability of a measurement result and the evaluation of the measurement uncertainty. In Brazil, the first two CT systems for dimensional applications were installed about a decade ago in two research centers. For years these two CT infrastructures for dimensional metrology allowed companies of different segments to benefit from the technique and made it possible for researchers to be involved in the field of CT for dimensional metrology. More recently, those promising initiatives have been drastically reduced for reasons such as the obsolescence of those CT infrastructures, despite the significant research efforts that have been observed in other venues. To reverse this negative outlook associated with the field of CT dimensional metrology in Brazil, this paper outlines an integrative framework for collaborative research and development in the subject, which encourages measures, e.g., to fund basic and applied researches, to train and educate people, and to support industries through measurement services and bespoke solutions.

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“…Both SNR and CNR have been widely used to quantify, optimise and simulate noise in industrial XCT measurements [47][48][49][50][51][52][53][54][55]. CNR is suggested as a method of quantifying optimal scan settings in ISO 15708-2 [45].…”

Section: Signal-to-noise and Contrast-to-noise Ratiosmentioning

confidence: 99%

Review of the influence of noise in X-ray computed tomography measurement uncertainty

Rodríguez-Sánchez

Thompson

Körner

et al. 2020

Precision Engineering

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Different aspects of noise in X-ray computed tomography (XCT) for industrial purposes are examined. An overview of the most common noise metrics is given, together with a description of XCT noise influence quantities. We address the current state of the art in understanding the contribution of noise to XCT measurement uncertainty, giving a chronological view of the different attempts that have been made to account for the contribution from noise to XCT measurement uncertainty. We conclude that approaches to estimating the contribution of noise to XCT measurement uncertainty that account for not only noise, but also other factors that affect image quality (e.g., scattering, beam hardening and blurring) are preferable to approaches that only account for noise.

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Comparison of surface-based and image-based quality metrics for the analysis of dimensional computed tomography data

Cited by 10 publications

References 12 publications

Sinogram interpolation to decrease acquisition time in X-ray computed tomography measurement of surface topography

Sinogram interpolation to decrease acquisition time in X-ray computed tomography measurement of surface topography

CT-based dimensional metrology developments in Brazil: Current status and outlook

Review of the influence of noise in X-ray computed tomography measurement uncertainty

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