Skip to main content

Advertisement

SpringerLink
Log in

Development and Validation of a Near-Infrared Optical System for Tracking Surgical Instruments

  • Systems-Level Quality Improvement
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Surgical navigation systems can help doctors maximize the accuracy of surgeries, minimize operation durations, avoid mistakes, and improve the survival chances of patients. The tracking of device is an important component in surgical navigation systems. However, commercial surgical tracking devices are expensive, thus hindering the development of surgical navigation systems, particularly in developing countries. Therefore, an accurate and low-cost near-infrared optical tracking system is presented in this study for the real-time tracking of surgical tools and for measuring and displaying the positions of these tools relative to lesions and other targets inside a patient’s body. A relative algorithm for the registration of surgical tools is also proposed in this paper to yield easy, safe, and precise tracking. Experiments are conducted to test the performance of the system. Results show that the mean square errors of the distances between the light-emitting points on the surgical tools are less than 0.3 mm, with the mean square error of distance between the tip and light-emitting points is less than 0.025 mm and that between two adjacent corner points is 0.2714 mm.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Ren, H., and Kazanzides, P., Investigation of attitude tracking using an integrated inertial and magnetic navigation system for hand-held surgical instruments. IEEE-ASME Trans Mech 17(2):210–217, 2012.

    Article  Google Scholar 

  2. Simpson, A. L., Burgner, J., Glisson, C. L., Herrell, S. D., Ma, B., Pheiffer, T. S., Webster, R. J., and Miga, M., Comparison study of intraoperative surface acquisition methods for surgical navigation. IEEE Trans Biomed Eng 60(4):1090–1099, 2013.

    Article  PubMed  Google Scholar 

  3. Wittmann, W., Wenger, T., Zaminer, B., and Lueth, T. C., Automatic correction of registration errors in surgical navigation systems. IEEE Trans Biomed Eng 58(10):2922–2930, 2011.

    Article  PubMed  Google Scholar 

  4. Vaccarella, A., De Momi, E., Enquobahrie, A., and Ferrigno, G., Unscented Kalman filter based sensor fusion for robust optical and electromagnetic tracking in surgical navigation. IEEE Trans Instrum Meas 62(7):2067–2081, 2013.

    Article  Google Scholar 

  5. Brouwer, O. R., Buckle, T., Bunschoten, A., Kuil, J., Vahrmeijer, A. L., Wendler, T., Valdés-Olmos, R. A., van der Poel, H. G., and van Leeuwen, F. W., Image navigation as a means to expand the boundaries of fluorescence-guided surgery. Phys Med Biol 57(10):3123, 2012.

    Article  PubMed  Google Scholar 

  6. West, J. B., and Maurer, C. R., Jr., Designing optically tracked instruments for image-guided surgery. IEEE Trans Med Imaging 23(5):533–545, 2004.

    Article  PubMed  Google Scholar 

  7. Maier-Hein, L., Mountney, P., Bartoli, A., Elhawary, H., Elson, D., Groch, A., Kolb, A., Rodrigues, M., Sorger, J., and Speidel, S., Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery. Med Image Anal 17(8):974–996, 2013.

    Article  CAS  PubMed  Google Scholar 

  8. Nakajima, Y., Dohi, T., Sasama, T., Momoi, Y., Sugano, N., Tamura, Y., Lim, S. H., Sakuma, I., Mitsuishi, M., and Koyama, T., Surgical tool alignment guidance by drawing two cross-sectional laser-beam planes. IEEE Trans Biomed Eng 60(6):1467–1476, 2013.

    Article  PubMed  Google Scholar 

  9. Maybank, S. J., and Faugeras, O. D., A theory of self-calibration of a moving camera. Int J Comput Vision 8(2):123–151, 1992.

    Article  Google Scholar 

  10. Luong, Q.-T., and Faugeras, O. D., Self-calibration of a moving camera from point correspondences and fundamental matrices. Int J Comput Vision 22(3):261–289, 1997.

    Article  Google Scholar 

  11. J.-Y. Bouguet, "Camera calibration toolbox for matlab," 2004

  12. Yang, R., Wang, Z., Liu, S., and Wu, X., Design of an accurate near infrared optical tracking system in surgical navigation. J Lightwave Technol 31(2):223–231, 2013.

    Article  Google Scholar 

  13. Wang, Z., Wu, W., Xu, X., and Xue, D., Recognition and location of the internal corners of planar checkerboard calibration pattern image. Appl Math Comput 185(2):894–906, 2007.

    Google Scholar 

  14. Melo, R., Barreto, J. P., and Falcao, G., A new solution for camera calibration and real-time image distortion correction in medical endoscopy–initial technical evaluation. IEEE Trans Biomed Eng 59(3):634–644, 2012.

    Article  PubMed  Google Scholar 

  15. Ito, M., and Ishii, A., A three-level checkerboard pattern (TCP) projection method for curved surface measurement. Pattern Recogn 28(1):27–40, 1995.

    Article  Google Scholar 

  16. Huang, X., Ren, J., Guiraudon, G., Boughner, D., and Peters, T. M., Rapid dynamic image registration of the beating heart for diagnosis and surgical navigation. IEEE Trans Med Imaging 28(11):1802–1814, 2009.

    Article  PubMed  Google Scholar 

  17. Shoham, M., Burman, M., Zehavi, E., Joskowicz, L., Batkilin, E., and Kunicher, Y., Bone-mounted miniature robot for surgical procedures: concept and clinical applications. IEEE Trans Robotic Autom 19(5):893–901, 2003.

    Article  Google Scholar 

  18. Lewis, J. T., Galloway, R. L., Jr., and Schreiner, S., An ultrasonic approach to localization of fiducial markers for interactive, image-guided neurosurgery. I. Principles. IEEE Trans Biomed Eng 45(5):620–630, 1998.

    Article  CAS  PubMed  Google Scholar 

  19. Stefansic, J. D., Bass, W. A., Hartmann, S. L., Beasley, R. A., Sinha, T. K., Cash, D. M., Herline, A. J., and Galloway, R. L., Design and implementation of a PC-based image-guided surgical system. Comput Meth Prog Bio 69(3):211–224, 2002.

    Article  Google Scholar 

  20. Deacon, G., Harwood, A., Holdback, J., Maiwand, D., Pearce, M., Reid, I., Street, M., and Taylor, J., The Pathfinder image-guided surgical robot. Proc Inst Mech Eng H J Eng Med 224(5):691–713, 2010.

    Article  CAS  Google Scholar 

  21. Mundeleer, L., Wikler, D., Leloup, T., and Warzée, N., Development of a computer assisted system aimed at RFA liver surgery. Comput Med Imag Grap 32(7):611–621, 2008.

    Article  Google Scholar 

  22. Wiles, A. D., and Peters, T. M., Target tracking errors for 5D and 6D spatial measurement systems. IEEE Trans Med Imaging 29(3):879–894, 2010.

    Article  PubMed  Google Scholar 

  23. Reijnders, K., Coppes, M., van Hulzen, A., Gravendeel, J., Van Ginkel, R., and Hoekstra, H., Image guided surgery: new technology for surgery of soft tissue and bone sarcomas. Eur J Surg Oncol 33(3):390–398, 2007.

    Article  CAS  PubMed  Google Scholar 

  24. Lin, Q., Yang, R., Cai, K., Guan, P., Xiao, W., and Wu, X., Strategy for accurate liver intervention by an optical tracking system. Biomed Opt Express 6(9):3287–3302, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

This research was funded by the National Natural Science Foundation of China under Grant No.61505037, the State Scholarship Fund under Grant CSC NO.201408440326, the Pearl River S&T Nova Program of Guangzhou under Grant No.2014 J2200049 and No.201506010035, the Guangdong Provincial Science and Technology Program under Grant No.2013B090600057, No.2014A020215006 and 2014A020212657, the Fundamental Research Funds for the Central Universities under Grant No.2014ZG003D, the Natural Scientific Foundation of Guangxi under Grant No.2015GXNSFBA139259.

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, South China University of Technology, Guangzhou, 510006, China

    Qinyong Lin, Rongqian Yang, Zhigang Wang & Jing Zhou

  2. School of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China

    Ken Cai

  3. College of Science, Guilin University of Technology, Guilin, 541004, China

    Huazhou Chen

Authors
  1. Qinyong Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ken Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rongqian Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Huazhou Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhigang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jing Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ken Cai.

Additional information

This article is part of the Topical Collection on Systems-Level Quality Improvement

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, Q., Cai, K., Yang, R. et al. Development and Validation of a Near-Infrared Optical System for Tracking Surgical Instruments. J Med Syst 40, 107 (2016). https://doi.org/10.1007/s10916-016-0462-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10916-016-0462-0

Keywords

Search

Navigation