Skip to main content
SpringerLink
Log in

Quantitative Assessments for Ultrasound Probe Calibration

  • Conference paper
  • First Online:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 (MICCAI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12904))

Abstract

Ultrasound probe calibration remains an area of active research but the science of validation has not received proportional attention in current literature. In this paper, we propose a framework to improve, assess, and visualize the quality of probe calibration. The basis of our framework is a heteroscedastic fiducial localization error (FLE) model that is physically quantifiable, used to i) derive an optimal calibration transform in the presence of heteroscedastic FLE, ii) assess the quality of a particular instance of probe calibration using a registration circuit, and iii) visualize the distribution of target registration error (TRE). The novelty of our work is the extension of the registration circuit to Procrustean point-line registration, and a demonstration that it produces a quantitative metric that correlates with true TRE. By treating ultrasound calibration as a heteroscedastic errors-in-variables regression instead of a least-squares regression, a more accurate calibration can be consistently obtained. Our framework has direct implication to many calibration techniques using point- and line-based calibration phantoms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Arun, K.S., Huang, T.S., Blostein, S.D.: Least-squares fitting of two 3-D point sets. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-9(5), 698–700 (1987)

    Google Scholar 

  2. Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)

    Article  Google Scholar 

  3. Chen, E.C.S., Peters, T.M., Ma, B.: Guided ultrasound calibration: where, how, and how many calibration fiducials. Int. J. Comput. Assist. Radiol. Surg. 11(6), 889–898 (2016)

    Article  Google Scholar 

  4. Chen, E.C.S., Peters, T.M., Ma, B.: Which point-line registration? In: Webster, R.J., III., Fei, B. (eds.) Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10135, pp. 70–82. International Society for Optics and Photonics, SPIE (2017)

    Google Scholar 

  5. Comeau, R.M., Fenster, A., Peters, T.M.: Integrated MR and ultrasound imaging for improved image guidance in neurosurgery. In: Hanson, K.M. (ed.) Medical Imaging 1998: Image Processing, vol. 3338, pp. 747–754. International Society for Optics and Photonics, SPIE (1998)

    Google Scholar 

  6. Danilchenko, A., Fitzpatrick, J.M.: General approach to first-order error prediction in rigid point registration. IEEE Trans. Med. Imaging 30(3), 679–693 (2011)

    Article  Google Scholar 

  7. Datteri, R.D.: Assessing registration quality via registration circuits. Ph.D. thesis, Vanderbilt University, Nashville, Tennessee, USA (2014)

    Google Scholar 

  8. Datteri, R.D., Dawant, B.M.: Estimation and reduction of target registration error. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012. LNCS, vol. 7512, pp. 139–146. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33454-2_18

    Chapter  Google Scholar 

  9. Fitzpatrick, J.M.: Fiducial registration error and target registration error are uncorrelated. In: Miga, M.I., Wong, K.H. (eds.) Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, vol. 7261, pp. 21–32. International Society for Optics and Photonics, SPIE (2009)

    Google Scholar 

  10. Fitzpatrick, J.M., West, J.B., Maurer, C.R.: Predicting error in rigid-body point-based registration. IEEE Trans. Med. Imaging 17(5), 694–702 (1998)

    Article  Google Scholar 

  11. Fusiello, A., Crosilla, F., Malapelle, F.: Procrustean point-line registration and the NPnP problem. In: 2015 International Conference on 3D Vision, pp. 250–255 (2015)

    Google Scholar 

  12. Gower, J.C., Dijksterhuis, G.B.: Procrustes Problems. Oxford University Press, Oxford (2004)

    Book  MATH  Google Scholar 

  13. He, K., Gkioxari, G., Dollár, P., Girshick, R.: Mask R-CNN. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2980–2988 (2017)

    Google Scholar 

  14. Horn, B.K.P.: Closed-form solution of absolute orientation using unit quaternions. J. Opt. Soc. Am. A 4(4), 629–642 (1987)

    Article  Google Scholar 

  15. Hsu, P.W., Prager, R.W., Gee, A.H., Treece, G.M.: Freehand 3D ultrasound calibration: a review. In: Sensen, C.W., Hallgrímsson, B. (eds.) Advanced Imaging in Biology and Medicine: Technology, Software Environments, Applications, pp. 47–84. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-540-68993-5_3

    Chapter  Google Scholar 

  16. Khamene, A., Sauer, F.: A novel phantom-less spatial and temporal ultrasound calibration method. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 65–72. Springer, Heidelberg (2005). https://doi.org/10.1007/11566489_9

    Chapter  Google Scholar 

  17. Lasso, A., Heffter, T., Rankin, A., Pinter, C., Ungi, T., Fichtinger, G.: PLUS: open-source toolkit for ultrasound-guided intervention systems. IEEE Trans. Biomed. Eng. 61(10), 2527–2537 (2014)

    Article  Google Scholar 

  18. Lindseth, F., Tangen, G.A., Langø, T., Bang, J.: Probe calibration for freehand 3-D ultrasound. Ultrasound Med. Biol. 29, 1607–1623 (2003)

    Article  Google Scholar 

  19. Ma, B., Moghari, M.H., Ellis, R.E., Abolmaesumi, P.: Estimation of optimal fiducial target registration error in the presence of heteroscedastic noise. IEEE Trans. Med. Imaging 29(3), 708–723 (2010)

    Article  Google Scholar 

  20. Matei, B.: Heteroscedastic errors-in-variables models in computer vision. Ph.D. thesis, Rutgers University (2001)

    Google Scholar 

  21. Matei, B., Meer, P.: Optimal rigid motion estimation and performance evaluation with bootstrap. In: Proceedings of 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 339–345 (1999)

    Google Scholar 

  22. Mercier, L., Langø, T., Lindseth, F., Collins, D.L.: A review of calibration techniques for freehand 3-D ultrasound systems. Ultrasound Med. Biol. 31(4), 449–471 (2005)

    Article  Google Scholar 

  23. Mozaffari, M.H., Lee, W.S.: Freehand 3-D ultrasound imaging: a systematic review. Ultrasound Med. Biol. 43, 2099–2124 (2017)

    Article  Google Scholar 

  24. Muratore, D.M., Galloway, R.L., Jr.: Beam calibration without a phantom for creating a 3-D freehand ultrasound system. Ultrasound Med. Biol. 27(11), 1557–1566 (2001)

    Google Scholar 

  25. Prager, R.W., Rohling, R.N., Gee, A.H., Berman, L.H.: Rapid calibration for 3-D freehand ultrasound. Ultrasound Med. Biol. 24(6), 855–869 (1998)

    Article  Google Scholar 

  26. Rousseau, F., Hellier, P., Barillot, C.: Confhusius: a robust and fully automatic calibration method for 3D freehand ultrasound. Med. Image Anal. 9(1), 25–38 (2005)

    Article  Google Scholar 

  27. Treece, G.M., Gee, A.H., Prager, R.W., Cash, C.J.C., Berman, L.H.: High-definition freehand 3-D ultrasound. Ultrasound Med. Biol. 29, 529–546 (2003)

    Article  Google Scholar 

  28. Zhang, H., Banovac, F., White, A., Cleary, K.: Freehand 3D ultrasound calibration using an electromagnetically tracked needle. In: Cleary, K.R., Galloway, R.L., Jr. (eds.) Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, vol. 6141, pp. 775–783. International Society for Optics and Photonics, SPIE (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Robarts Research Institute, Western University, London, ON, Canada

    Elvis C. S. Chen & Terry M. Peters

  2. School of Biomedical Engineering, Western University, London, ON, Canada

    Elvis C. S. Chen & Terry M. Peters

  3. Department of Medical Biophysics, Western University, London, ON, Canada

    Elvis C. S. Chen & Terry M. Peters

  4. School of Computing, Queen’s University, Kingston, ON, Canada

    Burton Ma

Authors
  1. Elvis C. S. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Burton Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Terry M. Peters
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elvis C. S. Chen .

Editor information

Editors and Affiliations

  1. Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    Marleen de Bruijne

  2. University of Basel, Allschwil, Switzerland

    Philippe C. Cattin

  3. Inria Nancy Grand Est, Villers-lès-Nancy, France

    Stéphane Cotin

  4. ICube, Université de Strasbourg, CNRS, Strasbourg, France

    Nicolas Padoy

  5. National Center for Tumor Diseases (NCT/UCC), Dresden, Germany

    Stefanie Speidel

  6. Tencent Jarvis Lab, Shenzhen, China

    Yefeng Zheng

  7. ICube, Université de Strasbourg, CNRS, Strasbourg, France

    Caroline Essert

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chen, E.C.S., Ma, B., Peters, T.M. (2021). Quantitative Assessments for Ultrasound Probe Calibration. In: de Bruijne, M., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021. MICCAI 2021. Lecture Notes in Computer Science(), vol 12904. Springer, Cham. https://doi.org/10.1007/978-3-030-87202-1_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-87202-1_35

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87201-4

  • Online ISBN: 978-3-030-87202-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation