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Industrial X-Ray Computed Tomography

Abstract

In this chapter, an identification and classification of influence factors in X-ray computed tomography metrology is given. A description of image artefacts commonly encountered in industrial X-ray computed tomography is presented together with their quantification. A survey of hardware and software methods developed for correcting image artefacts is presented.

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References

  • Abu Anas EM, Kim J, Lee S, Hasan Mdk (2011) Comparison of ring artifact removal methods using flat panel detector based CT images. Biomed Eng onLine 10:72

    Google Scholar 

  • Aloisi V, Carmignato S, Schlecht J, Ferley E (2017) Investigation on the effects of X-ray CT system geometrical misalignments on dimensional measurement errors. In: 7th conference on industrial computed tomography (iCT), 7–9 Feb, Leuven, Belgium

    Google Scholar 

  • Angel J, De Chiffre L, Kruth JP, Tan Y, Dewulf W (2015) Performance evaluation of CT measurements made on step gauges using statistical methodologies, CIRP J Manuf Sci Technol 11:68–72

    Google Scholar 

  • Angel J, De Chiffre L (2014) Comparison on computed tomography using industrial items. CIRP Ann Manuf Technol 63(1):473–476

    Google Scholar 

  • Arenhart F, Baldo CR, Fernandes TL,  Donatelli GD (2016a) Experimental investigation of the influencing factors on the structural resolution for dimensional measurements with CT systems. In: 6th conference on industrial computed tomography, Wels, p 12.

    Google Scholar 

  • Arenhart FA, Nardelli VC, Donatelli GD (2016b) Comparison of surface-based and image-based quality metrics for the analysis of dimensional computed tomography data. Case Stud Nondestruct Test Eval

    Google Scholar 

  • Bartscher M, Sato O, Härtig F, Neuschaefer-Rube U (2014) Current state of standardization in the field of dimensional computed tomography. Meas Sci Technol 25(6)

    Google Scholar 

  • Bartscher M, Staude A, Ehrig K, Ramsey A (2012) The influence of data filtering on dimensional measurements with CT. 18th WCNDT—World conference on nondestructive testing, pp 16–20 

    Google Scholar 

  • Bequé D, Nuyts J, Bormans G, Suetens P, Dupont P (2003) Characterization of pinhole SPECT acquisition geometry. IEEE Trans Med Imaging 22(5):599–612

    Google Scholar 

  • Bor D, Birgul O, Onal U, Olgar T (2016) Investigation of grid performance using simple image quality tests. J Med Phys 41(1):21–8

    Google Scholar 

  • Borges de Oliveira F, Stolfi A, Bartscher M, De Chiffre L (2016) Experimental investigation of surface determination process on multi-material components for dimensional computed tomography. Case Stud Nondestruct Test Eval 6(Part B):93–103. doi:10.1016/j.csndt.2016.04.003

  • Brunke O (2016) Recent developments of hard-and software for industrial CT systems. In: 6th conference on industrial computed tomography (iCT), 9–12 Feb, Wels, Austria

    Google Scholar 

  • Carmignato S, Aloisi V, Medeossi F, Zanini F, Savio E (2017) Influence of surface roughness on computed tomography dimensional measurements. CIRP Ann Manuf Technol 66(1):499–502. doi:10.1016/j.cirp.2017.04.067

  • Davis GR, Elliott JC (1997) X-ray microtomography scanner using time-delay integration for elimination of ring artefacts in the reconstructed image. Nucl Instrum Methods Phys Res Sect A 394(1-2):157–162

    Google Scholar 

  • De Chiffre L, Carmignato S, Kruth JP, Schmitt R, Weckenmann A (2014) Industrial applications of computed tomography. CIRP Annals 63(2):655–677. doi:10.1016/j.cirp.2014.05.011

  • Ferrucci M, Leach R, Giusca C, Carmignato S, Dewulf W (2015) Towards geometrical calibration of X-ray computed tomography systems—a review. Meas Sci Technol 26(August):92003. doi:10.1088/0957-0233/26/9/092003

  • Glover GH (1982) Compton scatter effects in CT reconstructions. Med Phys 9(6):860–867. Available at: http://www.ncbi.nlm.nih.gov/pubmed/7162472. Accessed 23 May 2016

  • Hemachandran K, Chetal AR (1986) X-ray K-absorption study of copper in malachite mineral. Physica Status Solidi (B) 136(1):181–185. Available at: http://doi.wiley.com/10.1002/pssb.2221360120. Accessed 24 Oct 2016

  • Hiller J, Maisl M, Reindl LM (2012) Physical characterization and performance evaluation of an X-ray micro-computed tomography system for dimensional metrology applications. Meas Sci Technol 23(8):85404. Available at: http://stacks.iop.org/0957-0233/23/i=8/a=085404?key=crossref.f16b74da17fdf2dcb54f5caf3bc9722e. Accessed 26 Apr 2016

  • Hunter A, McDavid W (2012) Characterization and correction of cupping effect artefacts in cone beam CT. Dentomaxillofac Radiol 41(3):217–223. Available at: http://www.birpublications.org/doi/abs/10.1259/dmfr/19015946. Accessed 26 Apr 2016

  • IEC (2003) IEC 62220-1 medical electrical equipment—characteristics of digital X-ray imaging devices—Part 1: determination of the detective quantum efficiency, Geneva, Switzerland. Available at: http://www.umich.edu/~ners580/ners-bioe_481/lectures/pdfs/2003-10-IEC_62220-DQE.pdf. Accessed 24 May 2016

  • Ihsan A, Heo SH, Cho SO (2007) Optimization of X-ray target parameters for a high-brightness microfocus X-ray tube. Nucl Instrum Methods Phys Res Sect B 264(2):371–377

    Article  Google Scholar 

  • JCGM (2008) JCGM 200 : 2008 international vocabulary of metrology—basic and general concepts and associated terms (VIM) vocabulaire international de métrologie—concepts fondamentaux et généraux et termes associés (VIM). In: International organization for standardization Geneva ISBN, 3(Vim), p 104. Available at: http://www.bipm.org/utils/common/documents/jcgm/JCGM_200_2008.pdf

  • Kasperl S, Bauscher I, Hassler U, Markert H, Schröpfer S (2002) Reducing artifacts in industrial 3D computed tomography (CT). In: Conference: proceedings of the vision, modeling, and visualization conference 2002, Erlangen, Germany, 20–22 Nov, pp 51–57

    Google Scholar 

  • Ketcham RA, Carlson WD (2001) Acquisition, optimiziation and interpretation of X-ray computed tomography imagery: applications to the geosciences. Comput Geosci 27:381–400

    Google Scholar 

  • Konstantinidis A (2011) Evaluation of digital X-ray detectors for medical imaging applications. Ph.D. thesis.University College London

    Google Scholar 

  • Krumm M, Kasperl S, Franz M (2008) Reducing non-linear artifacts of multi-material objects in industrial 3D computed tomography. NDT E Int 41(4):242–251. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0963869507001478. Accessed 26 Apr 2016

  • Kruth JP, Bartscher M, Carmignato S, Schmitt R, De Chiffre L, Weckenmann A (2011) Computed tomography for dimensional metrology.  CIRP Annals 60(2):821–842. doi:10.1016/j.cirp.2011.05.006

  • Kumar J, Attridge A, Wood PKC and Williams MA (2011) Analysis of the effect of cone-beam geometry and test object configuration on the measurement accuracy of a computed tomography scanner used for dimensional measurement. Meas Sci Technol 22(3)

    Google Scholar 

  • Kuusk J (2011) Dark signal temperature dependence correction method for miniature spectrometer modules. J Sens 2011:1–9. doi:10.1155/2011/608157

  • Landauer R (1989) Johnson-nyquist noise derived from quantum mechanical transmission. Physica D: Nonlinear Phenom 38(1–3):226–229. Available at: http://linkinghub.elsevier.com/retrieve/pii/0167278989901978. Accessed 26 Apr 2016

  • Lazurik V, Moskvin V, Tabata T (1998) Average depths of electron penetration: use as characteristic depths of exposure. IEEE Trans Nucl Sci 45(3):626–631. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=682461. Accessed 17 July 2016

  • Lifton JJ, Malcolm AA, McBride JW (2015) A simulation-based study on the influence of beam hardening in X-ray computed tomography for dimensional metrology. J X-ray Sci Technol 23(1):65–82

    Google Scholar 

  • Lifton JJ, Malcolm AA, McBride JW (2016) An experimental study on the influence of scatter and beam hardening in X-ray CT for dimensional metrology. Meas Sci Technol 27(1):15007

    Google Scholar 

  • Matern D, Herold F, Wenzel T (2016) On the influence of ring artifacts on dimensional measurement in industrial computed tomography. In: 6th conference on industrial computed tomography (iCT) 2016, 9–12 Feb 2016

    Google Scholar 

  • Mehranian A, Ay MR, Alam NR, Zaidi H (2010) Quantifying the effect of anode surface roughness on diagnostic X-ray spectra using Monte Carlo simulation. Med Phys 37(2):742

    Google Scholar 

  • Müller P, Hiller J, Cantatore A, Tosello G, De Chiffre L (2012) New reference object for metrological performance testing of industrial CT systems. In: Proceedings of the 12th euspen international conference

    Google Scholar 

  • Müller P, Hiller J, Dai Y, Andreasen JL, Hansen HN, De Chiffre L (2016) Estimation of measurement uncertainties in X-ray computed tomography metrology using the substitution method. CIRP J Manuf Sci Technol 7(3):222–232. Available at: http://linkinghub.elsevier.com/retrieve/pii/S1755581714000157  

  • Prell D, Kyriakou Y, Kalender WA (2009) Comparison of ring artifact correction methods for flat-detector CT. Phys Med Biol 54(12):3881–3895

    Article  Google Scholar 

  • Schuetz P, Jerjen I, Hofmann J, Plamondon M, Flisch A, Sennhauser U (2014) Correction algorithm for environmental scattering in industrial computed tomography.  NDT E Int Volume 64:59–64, ISSN 0963-8695, http://dx.doi.org/10.1016/j.ndteint.2014.03.002

  • Schörner K (2012) Development of methods for scatter artifact correction in industrial X-ray cone-beam computed tomography. Technische Universität München. Available at: http://mediatum.ub.tum.de/doc/1097730/document.pdf. Accessed 24 May 2016

  • Sijbers J and Postnov A (2004) Reduction of ring artefacts in high resolution micro-CT reconstructions. Phys Med Biol 49(14):N247–N253 

    Google Scholar 

  • Stachowiak GW, Batchelor AW (1993) Engineering tribology. Elsevier

    Google Scholar 

  • Stigler SM (1982) Poisson on the poisson distribution. Stat Probab Lett 1(1):33–35. Available at: http://linkinghub.elsevier.com/retrieve/pii/0167715282900104. Accessed 24 May 2016

  • Stolfi A, Thompson MK, Carli L, De Chiffre L (2016). Quantifying the Contribution of Post-Processing in Computed Tomography Measurement Uncertainty. Procedia CIRP 43:297–302. doi:10.1016/j.procir.2016.02.123  

  • Stolfi A, Kallasse M-H, Carli L, De Chiffre L. (2016). Accuracy Enhancement of CT Measurements using Data Filtering. In: Proceedings of the 6th Conference on Industrial Computed Tomography (iCT 2016)   

    Google Scholar 

  • Tan Y (2015) Scanning and post-processing parameter optimization for CT dimensional metrology. Ph.D. thesis, KU Leuven, Science, Heverlee, Belgium

    Google Scholar 

  • Thierry R, Miceli A, Hofmann J (2007) Hybrid simulation of scattering distribution in cone beam CT. In: DIR 2007—International symposium on digital industrial radiology and computed tomography, 25–27 June, Lyon, France

    Google Scholar 

  • Toft P (1996) The radon transform theory and implementation. Ph.D. thesis. Technical University of Denmark

    Google Scholar 

  • Tuy HK (1983) An inversion formula for cone-beam reconstruction. SIAM J Appl Math 43(3):546–552

    Google Scholar 

  • Umbaugh SE, Umbaugh SE (2011) Digital image processing and analysis: human and computer vision applications with CVIP tools. CRC Press

    Google Scholar 

  •  Van de Casteele E, Van Dyck D, Sijbers J, Raman E (2004) The effect of beam hardening on resolution in X-ray microtomography. In: Fitzpatrick JM, Sonka M (eds) roc. SPIE 5370, Medical Imaging 2004: Image Processing, 2089. International society for optics and photonics, pp 2089–2096 

    Google Scholar 

  • Van Gompel G, Van Slambrouck K, Defrise M, Batenburg KJ, Mey J, Sijbers J, Nuyts J (2011) Iterative correction of beam hardening artifacts in CT. Med Phys 38(S1):S36

    Google Scholar 

  • Van Nieuwenhove V, De Beenhouwer J, De Carlo F, Mancini L, Marone F, Sijbers J (2015) Dynamic intensity normalization using eigen flat fields in X-ray imaging. Opt Express 23(21):27975. Available at: https://www.osapublishing.org/abstract.cfm?URI=oe-23-21-27975. Accessed 24 May 2016

  • Verein Deutscher Ingenieure (2008) VDI/VDE 2630 Blatt 1.2: Computertomografie in der dimensionellen Messtechnik. Einflussgrößen auf das Messergebnis und Empfehlungen für dimensionelle Computertomografie-Messungen, pp 1–15

    Google Scholar 

  • Villarraga-Gómez H, Smith ST (2015) CT measurements and their estimated uncertainty: the significance of temperature and bias determination. In: Proceedings of 15th international conference on metrology and properties of engineering surfaces, University of North Carolina—Charlotte, USA, pp 509–515

    Google Scholar 

  • Villarraga-Gómez H, Clark D, Smith S (2016) Effect of the number of radiographs taken in CT for dimensional metrology. In: Proceedings of euspen’s 16th International Conference & Exhibition

    Google Scholar 

  • Weckenmann A, Krämer P (2013) Predetermination of measurement uncertainty in the application of computed tomography. Prod Lifecycle Manag: Geom Var 317–330

    Google Scholar 

  • Weiß D et al (2012) Geometric image distortion in flat-panel X-ray detectors and its influence on the accuracy of CT-based dimensional measurements. In: Conference on industrial computed tomography (iCT), Wels, pp 173–181

    Google Scholar 

  • Welkenhuyzen F (2016) Investigation of the accuracy of an X-ray CT scanner for dimensional metrology with the aid of simulations and calibrated artifacts. Ph.D. thesis, KU Leuven, Science, Heverlee, Belgium

    Google Scholar 

  • Wenig P, Kasperl S (2006) Examination of the Measurement Uncertainty on Dimensional Measurements by X-ray Computed Tomography, Proceedings of 9th European Congress on Non-Destructive Testing (ECNDT 2006)

    Google Scholar 

  • Wiegert J (2007) Scattered radiation in cone beam computed tomography: analysis, quantification and compensation. Publikations server der RWTH Aachen University

    Google Scholar 

  • Xi D et al (2010) The study of reconstruction image quality resulting from geometric error in micro-CT system. In: 2010 4th international conference on bioinformatics and biomedical engineering, pp 8–11

    Google Scholar 

  • Yagüe-Fabra JA, Ontiveros S, Jiménez R, Chitchian S, Tosello G, Carmignato S (2013) A 3D edge detection technique for surface extraction in computed tomography for dimensional metrology applications. CIRP Ann Manuf Technol 62(1):531–534. doi:10.1016/j.cirp.2013.03.016

  • Yousuf MA, Asaduzzaman M (2010) An efficient ring artifact reduction method based on projection data for micro-CT images. J Sci Res 2(1):37–45

    Google Scholar 

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Author information

Authors and Affiliations

  1. Technical University of Denmark (DTU), Produktionstorvet Building 425, 2800 Kgs, Lyngby, Denmark

    Alessandro Stolfi & Leonardo De Chiffre

  2. Fraunhofer Development Center for X-ray Technology (EZRT), Flugplatzstr. 75, Fürth, 90768, Germany

    Stefan Kasperl

Authors
  1. Alessandro Stolfi
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  2. Leonardo De Chiffre
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  3. Stefan Kasperl
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Corresponding author

Correspondence to Alessandro Stolfi .

Editor information

Editors and Affiliations

  1. Department of Management and Engineering, University of Padova, Vicenza, Italy

    Simone Carmignato

  2. Department of Mechanical Engineering, KU Leuven, Leuven, Belgium

    Wim Dewulf

  3. University of Nottingham, Nottingham, United Kingdom

    Richard Leach

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Stolfi, A., De Chiffre, L., Kasperl, S. (2018). Error Sources. In: Carmignato, S., Dewulf, W., Leach, R. (eds) Industrial X-Ray Computed Tomography. Springer, Cham. https://doi.org/10.1007/978-3-319-59573-3_5

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