Skip to main content
SpringerLink
Log in

3D Segmentation of Curved Needles Using Doppler Ultrasound and Vibration

  • Conference paper
Book cover Information Processing in Computer-Assisted Interventions (IPCAI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7915))

Abstract

A method for segmenting the 3D shape of curved needles in solid tissue is described. An actuator attached to the needle outside the tissue vibrates at frequencies between 600 Hz and 6500 Hz, while 3D power Doppler ultrasound imaging is applied to detect the resulting motion of the needle shaft and surrounding tissue. The cross section of the vibrating needle is detected across the series of 2D images produced by a mechanical 3D ultrasound transducer, and the needle shape is reconstructed by fitting a 3D curve to the resulting points. The sensitivity of segmentation accuracy to tissue composition, vibration frequency, and Doppler pulse repetition frequency (PRF) was examined. Comparison with manual segmentation demonstrates that this method results in an average error of 1.09 mm in ex vivo tissue. This segmentation method may be useful in the future for providing feedback on curved needle shape for control of robotic needle steering systems.

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 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 72.00
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aboofazeli, M., Abolmaesumi, P., Mousavi, P., Fichtinger, G.: A new scheme for curved needle segmentation in three-dimensional ultrasound images. In: IEEE Int. Symp. Biomedical Imaging: Nano to Macro, pp. 1067–1070 (2009)

    Google Scholar 

  2. Armstrong, G., Cardon, L., Vlkomerson, D., Lipson, D., Wong, J., Rodriguez, L.L., Thomas, J.D., Griffin, B.P.: Localization of needle tip with color doppler during pericardiocentesis: In vitro validation and initial clinical application. J. American Soc. Echocardiography 14, 29–37 (2001)

    Article  Google Scholar 

  3. Ayvaci, A., Yan, P., Xu, S., Soatto, S., Kruecker, J.: Biopsy needle detection in transrectal ultrasound. Comput. Med. Imag. Grap. 35(7), 653–659 (2011)

    Article  Google Scholar 

  4. Barva, M., Uhercik, M., Mari, J.M., Kybic, J., Duhamel, J.R., Liebgott, H., Hlavac, V., Cachard, C.: Parallel integral projection transform for straight electrode localization in 3-D ultrasound images. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 55(7), 1559–1569 (2008)

    Article  Google Scholar 

  5. Cheung, S., Rohling, R.: Enhancement of needle visibility in ultrasound-guided percutaneous procedures. Ultrasound Med. Biol. 30(5), 617–624 (2004)

    Article  Google Scholar 

  6. Cool, D.W., Gardi, L., Romagnoli, C., Saikaly, M., Izawa, J.I., Fenster, A.: Temporal-based needle segmentation algorithm for transrectal ultrasound prostate biopsy procedures. Med. Phys. 37(4), 1660–1673 (2010)

    Article  Google Scholar 

  7. Ding, M., Cardinal, H.N., Fenster, A.: Automatic needle segmentation in 3D ultrasound images using two orthogonal 2D image projections. Med. Phys. 30(2), 222–234 (2003)

    Article  Google Scholar 

  8. Ding, M., Fenster, A.: A real-time biopsy needle segmentation technique using hough transform. Med. Phys. 30(8), 2222–2233 (2003)

    Article  Google Scholar 

  9. Feld, R., Needleman, L., Goldberg, B.: Use of a needle-vibrating device and color doppler imaging for sonographically guided invasive procedures. Am. J. Roentgenology 168, 255–256 (1997)

    Article  Google Scholar 

  10. Fronheiser, M.P., Idriss, S.F., Wolf, P.D., Smith, S.W.: Vibrating interventional device detection using real-time 3-D color doppler. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 55(6), 1355–1362 (2008)

    Article  Google Scholar 

  11. Harmat, A., Rohling, R.N., Salcudean, S.E.: Needle tip localization using stylet vibration. Ultrasound Med. Biol. 32(9), 1339–1348 (2006)

    Article  Google Scholar 

  12. Holen, J., Waag, R.C., Gramiak, R.: Improved needle-tip visualization by color Doppler sonography. Am. J. Roentgenol. 156, 401–402 (1985)

    Google Scholar 

  13. Holen, J., Waag, R.C., Gramiak, R.: Representations of rapidly oscillating structures on the Doppler display. Ultrasound Med. Biol. 11(2), 267–272 (1985)

    Article  Google Scholar 

  14. Majewicz, A., Wedlick, T., Reed, K., Okamura, A.: Evaluation of robotic needle steering in ex vivo tissue. In: IEEE Int. Conf. Robotics Automation, pp. 2068–2073 (2010)

    Google Scholar 

  15. McAleavey, S.A., Rubens, D.J., Parker, K.J.: Doppler ultrasound imaging of magnetically vibrated brachytherapy seeds. IEEE Trans. Biomed. Eng. 50(2), 252–255 (2003)

    Article  Google Scholar 

  16. Neshat, H.R.S., Patel, R.V.: Real-time parametric curved needle segmentation in 3D ultrasound images. In: IEEE RAS EMBS Int. Conf. Biomedical Robotics Biomechatronics, pp. 670–675 (2008)

    Google Scholar 

  17. Novotny, P.M., Stoll, J.A., Vasilyev, N.V., del Nido, P.J., Dupont, P.E., Zickler, T.E., Howe, R.D.: GPU based real-time instrument tracking with three-dimensional ultrasound. Med. Im. Anal. 11(5), 458–464 (2007)

    Article  Google Scholar 

  18. Okazawa, S.H., Ebrahimi, R., Chuang, J., Rohling, R.N., Salcudean, S.E.: Methods for segmenting curved needles in ultrasound images. Med. Im. Anal. 10(3), 330–342 (2006)

    Article  Google Scholar 

  19. Qiu, W., Ding, M., Yuchi, M.: Needle segmentation using 3D quick randomized hough transform. In: IEEE Int. Conf. Intelligent Networks Intelligent Systems, pp. 449–452 (2008)

    Google Scholar 

  20. Reddy, K.E., Light, E.D., Rivera, D.J., Kisslo, J.A., Smith, S.W.: Color doppler imaging of cardiac catheters using vibrating motors. Ultrasonic Imaging 30, 247–250 (2008)

    Article  Google Scholar 

  21. Reed, K.B., Majewicz, A., Kallem, V., Alterovitz, R., Goldberg, K., Cowan, N.J., Okamura, A.M.: Robot-assisted needle steering. IEEE Robot. Autom. Mag. 18(4), 33–46 (2011)

    Article  Google Scholar 

  22. Rogers, A.J., Light, E.D., Smith, S.W.: 3-D ultrasound guidance of autonomous robot for location of ferrous shrapnel. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 56(7), 1301–1303 (2009)

    Article  Google Scholar 

  23. Uhercík, M., Kybic, J., Liebgott, H., Cachard, C.: Model fitting using ransac for surgical tool localization in 3D ultrasound images. IEEE Trans. Biomed. Eng. 57(8), 1907–1916 (2010)

    Article  Google Scholar 

  24. Wedlick, T.: Models and techniques to enhance the accuracy of robotic needle insertion. Ph.D. thesis, The Johns Hopkins University (2013)

    Google Scholar 

  25. Wei, Z., Gardi, L., Downey, D.B., Fenster, A.: Oblique needle segmentation and tracking for 3D TRUS guided prostate brachytherapy. Med. Phys. 32(9), 2928–2941 (2005)

    Article  Google Scholar 

  26. Wood, N.A., Shahrour, K., Ost, M.C., Riviere, C.N.: Needle steering system using duty-cycled rotation for percutaneous kidney access. In: Int. Conf. IEEE EMBS, pp. 5432–5435 (2010)

    Google Scholar 

  27. Zhou, H., Qiu, W., Ding, M., Songgen, Z.: Automatic needle segmentation in 3D ultrasound images using 3D improved hough transform. In: SPIE Medical Imaging: Image-Guided Procedures Modeling, vol. 6918, pp. 691821-1–691821-9 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Stanford University, Stanford, CA, USA

    Troy K. Adebar & Allison M. Okamura

Authors
  1. Troy K. Adebar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Allison M. Okamura
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Centre for Medical Image Computing, University College London, WC1E 6BT, London, UK

    Dean Barratt

  2. INRIA, Shacra, 59650, Villeneuve d’Ascq, France

    Stéphane Cotin

  3. School of Computing, Queen’s University, K7L 3N6, Kingston, ON, Canada

    Gabor Fichtinger

  4. Inserm/Université de Rennes 1, 2, Avenue du Pr. Léon Bernard CS 34317, 35043, Rennes, France

    Pierre Jannin

  5. Department of Computer Science, Technische Universität München, Boltzmannstrasse 3, 85748, Garching, Germany

    Nassir Navab

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Adebar, T.K., Okamura, A.M. (2013). 3D Segmentation of Curved Needles Using Doppler Ultrasound and Vibration. In: Barratt, D., Cotin, S., Fichtinger, G., Jannin, P., Navab, N. (eds) Information Processing in Computer-Assisted Interventions. IPCAI 2013. Lecture Notes in Computer Science, vol 7915. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38568-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38568-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38567-4

  • Online ISBN: 978-3-642-38568-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation