Skip to main content

Advertisement

Log in

EEG–MRI Co-registration and Sensor Labeling Using a 3D Laser Scanner

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

This paper deals with the co-registration of an MRI scan with EEG sensors. We set out to evaluate the effectiveness of a 3D handheld laser scanner, a device that is not widely used for co-registration, applying a semi-automatic procedure that also labels EEG sensors. The scanner acquired the sensors’ positions and the face shape, and the scalp mesh was obtained from the MRI scan. A pre-alignment step, using the position of three fiducial landmarks, provided an initial value for co-registration, and the sensors were automatically labeled. Co-registration was then performed using an iterative closest point algorithm applied to the face shape. The procedure was conducted on five subjects with two scans of EEG sensors and one MRI scan each. The mean time for the digitization of the 64 sensors and three landmarks was 53 s. The average scanning time for the face shape was 2 min 6 s for an average number of 5,263 points. The mean residual error of the sensors co-registration was 2.11 mm. These results suggest that the laser scanner associated with an efficient co-registration and sensor labeling algorithm is sufficiently accurate, fast and user-friendly for longitudinal and retrospective brain sources imaging studies.

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

Access this article

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

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  1. Adjamian, P., G. R. Barnes, A. Hillebrand, I. E. Holliday, K. D. Singh, P. L. Furlong, E. Harrington, C. W. Barclay, and P. J. G. Route. Co-registration of magnetoencephalography with magnetic resonance imaging using bite-bar-based fiducials and surface-matching. Clin. Neurophysiol. 115:691–698, 2004.

    Article  CAS  PubMed  Google Scholar 

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

    Article  Google Scholar 

  3. Barber, C. B., D. P. Dobkin, and H. T. Huhdanpa. The Quickhull algorithm for convex hulls. ACM Trans. Math. Softw. 22(4):69–483, 1996.

    Article  Google Scholar 

  4. Baysal, U., and G. Sengül. Single camera photogrammetry system for EEG electrode identification and localization. Ann. Biomed. Eng. 38(4):1539–1547, 2010.

    Article  PubMed  Google Scholar 

  5. Besl, P. J., and N. D. McKay. A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 4:239–256, 1992.

    Article  Google Scholar 

  6. Brinkmann, B., T. O’Brien, A. Dresner, T. Lagerlund, W. Sharbrough, and A. Robb. Scalp-recorded EEG localization in MRI volume data. Brain Topogr. 10(4):245–253, 1998.

    Article  CAS  PubMed  Google Scholar 

  7. Dennis, J. E., and R. B. Schnabel. Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Philadelphia: Society for Industrial and Applied Mathematics, 1996, p. 378.

    Google Scholar 

  8. Gouws, A. D., and W. Woods. Enhanced co-registration of MEG to MRI using a 3D Camera. Neuroimage 47:S39–S41, 2009.

    Article  Google Scholar 

  9. Hébert, P. A self-referenced hand-held range sensor. In: Proceedings of Third IEEE International Conference on 3-D Digital Imaging and Modeling, Québec City, 2001, pp. 5–12.

  10. Hébert, P., E. Saint-Pierre, and D. Tubic. Auto-referenced system and apparatus for three-dimensional scanning. U.S. Patent 2008/0201101 A1, Aug 21, 2008.

  11. Hu, G., J. Xu, L. Miao, and Q. Peng. Bilateral estimation of vertex normal for point-sampled models. Lect. Notes Comput. Sci. 3480:758–768, 2005.

    Article  Google Scholar 

  12. Huppertz, H., M. Otte, C. Grimm, R. Kriesteva-Feige, T. Mergner, and C. Lücking. Estimation of the accuracy of a surface matching technique for registration of EEG and MRI data. Electroencephalogr. Clin. Neurophysiol. 106:409–415, 1998.

    Article  CAS  PubMed  Google Scholar 

  13. Jiang, H., R. A. Robb, and K. S. Holton. A new approach to 3-D registration of multimodality medical images by surface matching. Visualization in biomedical computing. Proc. SPIE Int. Soc. Opt. Eng. 1808:196–213, 1992.

    Google Scholar 

  14. Koessler, L., L. Maillard, A. Benhadid, J. P. Vignal, M. Braun, and H. Vespignani. Spatial localization of EEG electrodes. Neurophysiol. Clin. 37:97–102, 2007.

    Article  CAS  PubMed  Google Scholar 

  15. Koessler, L., A. Benhadid, L. Maillard, J. P. Vignal, J. Felblinger, H. Vespignani, and M. Braun. Automatic localization and labeling of EEG sensors (ALLES) in MRI volume. Neuroimage 41:914–923, 2008.

    Article  CAS  PubMed  Google Scholar 

  16. Koessler, L., C. Benar, L. Maillard, J. M. Badier, J. P. Vignal, F. Bartolomei, P. Chauvel, and M. Gavaret. Source localization of ictal epileptic activity investigated by high resolution EEG and validated by SEEG. Neuroimage 51(2):642–653, 2010.

    Article  PubMed  Google Scholar 

  17. Koessler, L., T. Cecchin, E. Ternisien, and L. Maillard. 3D handheld laser scanner based approach for automatic identification and localization of EEG sensors. In: Proceedings of 32nd International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina, 2010, pp. 3707–3710.

  18. Kozinska, D., O. Tretiak, J. Nissanov, and C. Ozturk. Multidimensional alignment using the Euclidean distance transform. Graph. Model Image Process. 59(6):373–387, 1997.

    Article  Google Scholar 

  19. Kozinska, D., F. Carducci, and K. Nowinski. Automatic alignment of EEG/MEG and MRI data sets. Clin. Neurophysiol. 112:1553–1561, 2001.

    Article  CAS  PubMed  Google Scholar 

  20. Lamm, C., C. Windischberger, U. Leodolter, E. Moser, and H. Bauer. Co-registration of EEG and MRI data using matching of spline interpolated and MRI-segmented reconstructions of the scalp surface. Brain Topogr. 14(2):93–100, 2001.

    Article  CAS  PubMed  Google Scholar 

  21. Le, J., M. Lu, E. Pellouchoud, and A. Gevins. A rapid method for determining standard 10/10 electrode positions for high resolution EEG studies. Electroencephalogr. Clin. Neurophysiol. 106:554–558, 1998.

    Article  CAS  PubMed  Google Scholar 

  22. Maillard, L., L. Koessler, S. Colnat-Coulbois, J. P. Vignal, V. Louis-Dorr, P. Y. Marie, and H. Vespignani. Combined SEEG and source localisation study of temporal lobe schizencephaly and polymicrogyria. Clin. Neurophysiol. 120(9):1628–1636, 2009.

    Article  CAS  PubMed  Google Scholar 

  23. Marquardt, D. W. An algorithm for least squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11(2):431–441, 1963.

    Article  Google Scholar 

  24. Maurer, C. R., G. B. Aboutanos, B. M. Dawant, R. J. Maciunas, and J. M. Fitzpatrick. Registration of 3-D images using weighted geometrical features. IEEE Trans. Med. Imaging 15(6):836–849, 1996.

    Article  CAS  PubMed  Google Scholar 

  25. Michel, C. M., M. M. Murray, G. Lantz, S. Gonzalez, L. Spinelli, and R. de Grave Peralta. EEG source imaging. Clin. Neurophysiol. 115(10):2195–2222, 2004.

    Article  PubMed  Google Scholar 

  26. Noirhomme, Q., M. Ferrant, Y. Vandermeeren, E. Olivier, B. Macq, and O. Cuisenaire. Registration and real-time visualization of transcranial magnetic stimulation with 3-D MR images. IEEE Trans. Biomed. Eng. 51:1994–2005, 2004.

    Article  PubMed  Google Scholar 

  27. Péchaud, M., R. Keriven, T. Papadopoulo, and J. M. Badier. Automatic labeling of EEG electrodes using combinatorial optimization. In: Proceedings of 29th International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France, 2007, pp. 4398–4401.

  28. Pelizzari, C. A., G. T. Y. Chen, D. R. Spelbring, R. R. Weichselbaum, and C. T. Chen. Accurate three-dimensional registration of CT, PET, and/or MR images of the brain. J. Comput. Assist. Tomogr. 13:20–26, 1989.

    Article  CAS  PubMed  Google Scholar 

  29. Rusinkiewicz, S., and M. Levoy. Efficient variants of the ICP algorithm. In: Proceedings of International Conference on Recent Advances in 3-D Digital Imaging and Modelling, Québec, 2001, pp. 145–152.

  30. Sijbers, J., B. Vanrumste, G. Van Hoey, P. Boon, M. Verhoye, A. Van, D. der Linden, and Van Dyck. Automatic localization of EEG electrode markers within 3D MR data. Magn. Reson. Imaging 18:485–488, 2000.

    Article  CAS  PubMed  Google Scholar 

  31. Singh, K. D., I. E. Holliday, P. L. Furlong, and G. F. A. Harding. Evaluation of MRI-MEG/EEG co-registration strategies using Monte Carlo simulation. Electroencephalogr. Clin. Neurophysiol. 102:81–85, 1997.

    Article  CAS  PubMed  Google Scholar 

  32. Špiclin, Z., S. W. Warfield, B. Likar, and F. Pernuš. Registration of MRI and EEG based on internal and external anatomical similarities. In: Proceedings of 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Pt 1, 2008, pp. 762–770.

  33. Whalen, C., E. L. Maclin, M. Fabiani, and G. Gratton. Validation of a method for coregistering scalp recording locations with 3D structural MR images. Hum. Brain Mapp. 29(11):1288–1301, 2008.

    Article  PubMed  Google Scholar 

  34. Zhang, Z. Iterative point matching for registration of free-form curves and surfaces. Int. J. Comput. Vis. 13:119–152, 1994.

    Article  Google Scholar 

Download references

Acknowledgments

This study was supported by the French Ministry of Health (PHRC 17-05, 2009). The authors gratefully acknowledge the participation of the healthy subjects involved in this study. The authors also thank Prof. M. Braun and J. Felblinger (IADI Laboratory, INSERM U947) for the MRI data acquisition and review.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. Cecchin.

Additional information

Associate Editor Ioannis A. Kakadiaris oversaw the review of this article.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Koessler, L., Cecchin, T., Caspary, O. et al. EEG–MRI Co-registration and Sensor Labeling Using a 3D Laser Scanner. Ann Biomed Eng 39, 983–995 (2011). https://doi.org/10.1007/s10439-010-0230-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-010-0230-0

Keywords

Navigation