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A Comparative Evaluation of Two Scanning Modalities in Industrial Cone-Beam Computed Tomography

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Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

This paper discusses two scanning modalities for Industrial Cone-Beam Computed Tomography (ICBCT) and their comparative evaluation. The first conventional mode scans an object when it is stationary then it moves by an angular step and stops for scanning (Start-Stop mode). The second mode acquires projections on the fly while the object is in a steady motion. The second mode of acquisition of projection data is aimed at reducing overall scanning time with an acceptable level of systemic artifacts. Data generated in both modalities are digital radiographs, which serve as inputs for the generation of CT images. Evaluation of 2D projections acquired in both modalities was analyzed quantitatively to determine their comparative quality. Cone-beam CT has been implemented using the FDK algorithm on all acquired data sets. Subsequently, CT images from both modalities are analytically assimilated in terms of statistical parameters like line profile and SNR for comparative quality analysis. Reduction in scanning time from 3600 to 362 s was successfully achieved, however, system artifact generated due to asynchronous acquisition in the second modality was observed. The method to minimize systemic artifact generated in the second modality is discussed and implemented. Results before system artifact correction and after corrections are shown in the paper. The minimum time of 2π rotation motion for data acquisition without deteriorating reconstructed image quality for defined acquisition parameter has been estimated.

Keywords

  • Industrial computed tomography (ICT)
  • Non-destructive testing and evaluation (NDT/E)
  • Cone beam
  • Scanning time
  • Angular correction
  • Continuous scan
  • Quick scan
  • Scanning mode

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References

  1. Ritman EL (2004) Micro-computed tomography—current status and developments. Annu Rev Biomed Eng 6:185–208. https://doi.org/10.1146/annurev.bioeng.6.040803.140130

    CrossRef  Google Scholar 

  2. Jian F, Hongnian L, Bing L, Lei Z, Jingjing S (2007) X-CT imaging method for large objects using double offset scan mode. Nucl Instrum Methods Phys Res Sect A Accel Spectrom Detect Assoc Equip 575(3):519–523. https://doi.org/10.1016/j.nima.2007.03.008

  3. Toyokawa H, Kanada H, Kaihori T, Koike M, Yamada K (2008) Application of high-energy photon CT system with laser-compton scattering to non-destructive test. IEEE Trans Nucl Sci 55(6):3571–3578. https://doi.org/10.1109/TNS.2008.2006982

    CrossRef  Google Scholar 

  4. Lima I, Assis JT, Apoloni CR, Mendonça De Souza SMF, Duarte MEL, Lopes RT (2009) Non-destructive imaging materials investigation by microfocus 3D X-ray computed tomography. IEEE Trans Nucl Sci 56(3):1448–1453. https://doi.org/10.1109/TNS.2009.2013241

    CrossRef  Google Scholar 

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

    CrossRef  Google Scholar 

  6. Chul Lee S, Kyung Kim H, Kon Chun I, Hye Cho M, Yeol Lee S, Hyoung Cho M (2003) A flat-panel detector based micro-CT system: performance evaluation for small-animal imaging

    Google Scholar 

  7. Kak A, Slaney M (2001) Principles of computerized tomographic imaging. Society of Industrial and Applied Mathematics

    Google Scholar 

  8. du Plessis A, le Roux SG, Guelpa A (2016) Comparison of medical and industrial X-ray computed tomography for non-destructive testing. Case Stud Nondestr Test Eval 6:17–25. https://doi.org/10.1016/j.csndt.2016.07.001

    CrossRef  Google Scholar 

  9. Srinivasan VM et al (2018) Fast acquisition cone-beam computed tomography: Initial experience with a 10 s protocol. J Neurointerv Surg 10(9):916–920. https://doi.org/10.1136/neurintsurg-2017-013475

    CrossRef  Google Scholar 

  10. Du Plessis A, Rossouw P (2015) X-ray computed tomography of a titanium aerospace investment casting. Case Stud Nondestruct Test Eval 3:21–26. https://doi.org/10.1016/j.csndt.2015.03.001

    CrossRef  Google Scholar 

  11. Fu J, Jiang B, Li B, Li P, Wang Q (2010) Methods determining the angular increment of a continuous scan cone-beam CT system. IEEE Trans Nucl Sci 57(3), part 1:1071–1076. https://doi.org/10.1109/TNS.2010.2044662

  12. Yang M et al (2013) Extra projection data identification method for fast-continuous-rotation industrial cone-beam CT. J Xray Sci Technol 21(4):467–479. https://doi.org/10.3233/XST-130402

    CrossRef  Google Scholar 

  13. Seibert (2008) Digital radiography: image quality and radiation dose

    Google Scholar 

  14. Yu L et al (2009) Radiation dose reduction in computed tomography: techniques and future perspective. Imaging Med 1(1):65–84. https://doi.org/10.2217/iim.09.5

    CrossRef  Google Scholar 

  15. Medical x-ray tubes canon electron tubes & devices Co. https://etd.canon/en/product/category/xray/medical.html. Accessed Oct 11 2020

  16. Vock P, Kalender WA (2001) Computed tomography: fundamentals, system technology, image quality, applications (with CD-ROM). Eur Radiol Eur Radiol 11:1855.https://doi.org/10.1007/s003300100898

  17. Industrial x-ray tubes canon electron tubes & devices co. https://etd.canon/en/product/category/xray/industry.html. Accessed Oct 11 2020

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

    CrossRef  Google Scholar 

  19. Lee S, Vinegoni C, Sebas M, Weissleder R (2014) Automated motion artifact removal for intravital microscopy, without a priori information. Sci Rep 4. https://doi.org/10.1038/srep04507

  20. Spin-Neto R, Wenzel A (2016) Patient movement and motion artefacts in cone beam computed tomography of the dentomaxillofacial region: a systematic literature review. Oral Surg Oral Med Oral Pathol Oral Radiol 121(4): 425–433. Mosby Inc. https://doi.org/10.1016/j.oooo.2015.11.019

  21. Seeram E (2010) Computed tomography: physical principles and recent technical advances. J Med Imaging Radiat Sci 41(2):87–109. https://doi.org/10.1016/j.jmir.2010.04.001

    CrossRef  Google Scholar 

  22. Kumar U, Ramakrishna GS, Pendharkar AS, Kailas S (2003) A statistical correction method for minimization of systemic artefact in a continuous-rotate X-ray based industrial CT system. Nucl Instrum Methods Phys Res Sect A Accel Spectrom Detect Assoc Equip 515(3):829–839. https://doi.org/10.1016/j.nima.2003.07.019

  23. Yang M, Liu J, Li Z, Liang L, Wang X, Gui Z (2016) Locating of 2π-projection view and projection denoising under fast continuous rotation scanning mode of micro-CT. Neurocomputing 207:335–345. https://doi.org/10.1016/j.neucom.2016.05.018

    CrossRef  Google Scholar 

  24. Starman J (2010) Lag correction in amorphous silicon flat-panel x-ray computed tomography

    Google Scholar 

  25. Snoeren RM (2012) Physics-based optimization of image quality in 3D x-ray flat-panel cone-beam imaging

    Google Scholar 

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Correspondence to Anant Mitra .

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Mitra, A., Acharya, R., Kumar, U. (2022). A Comparative Evaluation of Two Scanning Modalities in Industrial Cone-Beam Computed Tomography. In: Mandayam, S., Sagar, S.P. (eds) Advances in Non Destructive Evaluation. NDE 2020. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-9093-8_9

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  • DOI: https://doi.org/10.1007/978-981-16-9093-8_9

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