Skip to main content

Advertisement

SpringerLink
Log in

Fast and accurate registration of cranial CT images with A-mode ultrasound

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Within the CRANIO project, a navigation module based on preoperative computed tomography (CT) data was developed for Computer and Robot Assisted Neurosurgery. The approach followed for non-invasive user-interactive registration of cranial CT images with the physical operating space consists of surface-based registration following pre-registration based on anatomical landmarks. Surface-based registration relies on bone surface points digitized transcutaneously by means of an optically tracked A-mode ultrasound (US) probe. As probe alignment and thus bone surface point digitization may be time-consuming, we investigated how to obtain high registration accuracy despite inaccurate pre-registration and a limited number of digitized bone surface points. Furthermore, we aimed at efficient man-machine-interaction during the probe alignment process. Finally, we addressed the problem of registration plausibility estimation in our approach.

Method

We modified the Iterative Closest Point (ICP) algorithm, presented by Besl and McKay and frequently used for surface-based registration, such that it can escape from local minima of the cost function to be iteratively minimized. The random-based ICP (R-ICP) we developed is less influenced by the quality of the pre-registration as it can escape from local minima close to the starting point for iterative optimization in the 6D domain of rigid transformations. The R-ICP is also better suited to approximate the global minimum as it can escape from local minima in the vicinity of the global minimum, too. Furthermore, we developed both CT-less and CT-based probe alignment tools along with appropriate man-machine strategies for a more time-efficient palpation process. To improve registration reliability, we developed a simple plausibility test based on data readily available after registration.

Results

In a cadaver study, where we evaluated the R-ICP algorithm, the probe alignment tools, and the plausibility test, the R-ICP algorithm consistently outperformed the ICP algorithm. Almost no influence of the pre-registration on the final R-ICP registration accuracy could be observed. The probe alignment tools were judged to be useful and allowed for the digitization of 18 bone surface points within 2 min on average. The plausibility test was helpful to detect poor registration accuracy.

Conclusion

The R-ICP algorithm can provide high registration accuracy despite inaccurate pre-registration and a very limited number of data points. R-ICP registration was shown to be practical and robust versus the quality of the pre-registration. Time-efficiency of the cranial palpation process may be greatly increased and should encourage clinical acceptance.

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

Similar content being viewed by others

References

  1. Amin DV, Kanade T, DiGioia AM III, Jaramaz B (2003) Ultrasound registration of the bone surface for surgical navigation. Comput Aided Surg 8(1): 1–16

    Article  PubMed  Google Scholar 

  2. Amstutz C, Caversaccio M, Kowal J, Bächler R, Nolte LP, Häusler R, Styner M (2003) A-mode ultrasound-based registration in computer-aided surgery on the skull. Arch Otolaryngol Head Neck Surg 129: 1310–1316

    Article  PubMed  Google Scholar 

  3. Bächler R, Bunke H, Nolte LP (2001) Restricted surface matching—numerical optimization and technical evaluation. Comput Aided Surg 6(3): 143–152

    PubMed  Google Scholar 

  4. Bast P, Engelhardt M, Lauer W, Schmieder K, Rohde V, Radermacher K (2003) Identification of milling parameters for manual cutting of bicortical bone structures. Comput Aided Surg 8(5): 257–263

    Article  PubMed  CAS  Google Scholar 

  5. Bast P, Popovic A, Wu T, Heger S, Engelhardt M, Lauer W, Radermacher K, Schmieder K (2006) Robot- and computer-assisted craniotomy: resection planning, implant modelling and robot safety. Int J Med Robot 2(2): 168–178

    PubMed  CAS  Google Scholar 

  6. Besl PJ, McKay ND (1992) A method for registration of 3d shapes. IEEE Trans PAMI 14(2): 239–256

    Google Scholar 

  7. Chetverikov D, Svirko D, Stepanov D, Krsek P (2002) The trimmed iterative closest point algorithm. Proc ICPR 3: 545–548

    Google Scholar 

  8. Eggers G, Mühling J, Marmulla R (2006) Image-to-patient registration techniques in head surgery. Int J Oral Maxillofac Surg 35: 1081–1095

    Article  PubMed  CAS  Google Scholar 

  9. Follmann A, Popovic A, Wu T, Cunha Cruz VVC, Schröder K, Ibach B, Radermacher K (2007) CRANIO system for robot and computer assisted removal of calvarial tumors. Int J CARS 2(l): 484–485

    Google Scholar 

  10. Friedman JH, Baskett F, Shustek LJ (1975) An algorithm for finding nearest neighbors. IEEE Trans Comput 24: 1000–1006

    Article  Google Scholar 

  11. Glozman D, Shoham M, Fischer A (2001) A surface-matching technique for robot-assisted registration. Comput Aided Surg 6(5): 259–269

    Article  PubMed  CAS  Google Scholar 

  12. Granger S, Pennec X, Roche A (2001) Rigid point-surface registration using oriented points and an em variant of icp for computer guided oral implantology. Technical report 4169, INRIA

  13. Grunert P, Darabi K, Espinosa J, Filippi R (2003) Computer aided navigation in neurosurgery. Neurosurg Rev 26: 73–99

    Article  PubMed  CAS  Google Scholar 

  14. Guinand N, Amstutz CA, Kowal J, Nolte LP, Häusler R, Caversaccio M (2001) Noninvasive registration in head surgery by A-mode ultrasound. In: Proc CAOS, p 81

  15. Heger S, Radermacher K (2003) Automatic calibration procedure for optically tracked A-mode ultrasound based registration. In: Proc. CAOS, pp 138–139

  16. Heger S, Portheine F, Ohnsorge JAK, Schkommodau E, Radermacher K (2005) User interactive registration of bone with A-mode ultrasound. IEEE Eng Med Biol Mag 24(2): 85–95

    Article  PubMed  Google Scholar 

  17. Horn BKP (1987) Closed-form solution of absolute orientation using unit quaternions. J Opt Soc Am A 4(4): 629–642

    Article  Google Scholar 

  18. Maintz JBA, Viergever MA (1998) A survey of medical image registration. Med Image Anal 2(1): 1–37

    Article  PubMed  CAS  Google Scholar 

  19. Masuda T, Sakaue K, Yokoya N (1996) Registration and integration of multiple range images for 3D model reconstruction. Proc ICPR 1: 879–883

    Google Scholar 

  20. Maurer CR Jr, Fitzpatrick JM, Wang MY, Galloway RL Jr, Maciunas RJ, Allen GS (1997) Registration of head volume images using implantable fiducial markers. IEEE Trans Med Imag 16: 447–462

    Article  Google Scholar 

  21. Maurer CR Jr, Maciunas RJ, Fitzpatrick JM (1998) Registration of head CT images to physical space using a weighted combination of points and surfaces. IEEE Trans Med Imaging 17(5): 753–761

    Article  PubMed  Google Scholar 

  22. Maurer CR Jr, Gaston RP, Hill DLG, Gleeson MJ, Taylor MG, Fenlon MR, Edwards PJ, Hawkes DJ (1999) AcouStick: a tracked a-mode ultrasonography system for registration in image-guided surgery. In: Proc MICCAI. LNCS, vol 1679, pp 953–962

  23. Popovic A, Engelhardt M, Wu T, Portheine F, Schmieder K, Radermacher K (2003) CRANIO—Computer assisted planning for navigated and robot assisted surgery on the skull. In: Proc CARS, pp 1269–1275

  24. Popovic A, Engelhardt M, Heger S, Radermacher K (2005) Efficient non-invasive registration with a-mode ultrasound in skull surgery: method and first clinical trials. In: Proc CARS, pp 821–826

  25. Pulli K (1999) Multiview registration for large data sets. In: Proc 3DIM, pp 160–168

  26. Rusinkiewicz S, Levoy M (2001) Efficient variants of the ICP algorithm. In: Proc 3DIM, pp 145–152

  27. Schreiner S, Galloway RL Jr, Lewis JT, Bass WA, Muratore DM (1998) An ultrasonic approach to localization of fiducial markers for interactive, image-guided neurosurgery–Part II: Implementation and automation. IEEE Trans Biomed Eng 45(5): 631–641

    Article  PubMed  CAS  Google Scholar 

  28. Simon D (1996) Fast and accurate shape-based registration. Doctoral Dissertation, Robotics Institute, Carnegie Mellon University

  29. Wolfsberger S, Rössler K, Regatschnig R, Ungersböck K (2002) Anatomical landmarks for image registration in frameless stereotactic neuronavigation. Neurosurg Rev 25: 68–72

    Article  PubMed  Google Scholar 

  30. Wu T, Engelhardt M, Fieten L, Popovic A, Radermacher K (2006) Anatomically constrained deformation for design of cranial implant: methodology and validation. In: Proc MICCAI. LNCS, vol 4190, pp 9–16

  31. Zhang Z (1994) Iterative point matching for registration of free-form curves and surfaces. Int J Comput Vision 13(2): 119–152

    Article  Google Scholar 

  32. Zinßer T, Schmidt J, Niemann H (2003) Performance analysis of nearest neighbor algorithms for icp registration of 3d point sets. In: Proc VMV, pp 199–206

Download references

Author information

Authors and Affiliations

  1. Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany

    Lorenz Fieten, Lamija Pasalic, Klaus Radermacher & Stefan Heger

  2. Department of Neurosurgery, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany

    Kirsten Schmieder

  3. Clinic for Neurosurgery, Ruhr University Bochum, Bochum, Germany

    Martin Engelhardt

Authors
  1. Lorenz Fieten
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kirsten Schmieder
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Martin Engelhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lamija Pasalic
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Klaus Radermacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Stefan Heger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lorenz Fieten.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fieten, L., Schmieder, K., Engelhardt, M. et al. Fast and accurate registration of cranial CT images with A-mode ultrasound. Int J CARS 4, 225–237 (2009). https://doi.org/10.1007/s11548-009-0288-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-009-0288-z

Keywords

Search

Navigation