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Registration of MR to Percutaneous Ultrasound of the Spine for Image-Guided Surgery

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Computational Methods and Clinical Applications for Spine Imaging

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 17))

Abstract

One of the main limitations of today’s navigation systems for spine surgery is that they often are not available until after the bone surface has been exposed. Also, they lack the capability of soft tissue imaging, both preoperatively and intraoperatively. The use of ultrasound has been proposed to overcome these limitations. By registering preoperative magnetic resonance (MR) images to intraoperative percutaneous ultrasound images, navigation can start even before incision. We therefore present a method for registration of MR images to ultrasound images of the spine. The method is feature-based and consists of two steps: segmentation of the bone surfaces from both the ultrasound images and the MR images, followed by rigid registration using a modified version of the Iterative Closest Point algorithm. The method was tested on data from a healthy volunteer, and the data set was successfully segmented and registered with an accuracy of \(3.67\pm 0.38\) mm.

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References

  1. Askeland, C., et al.: CustusX: A Research application for image-guided therapy. MIDAS J. 1–8 (2011). Systems and Architectures for Computer Assisted Interventions 2011. http://www.midasjournal.org/browse/journal/60

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

    Article  Google Scholar 

  3. Fedorov, A., et al.: 3D slicer as an image computing platform for the quantitative imaging network. Magn. Reson. Imaging 30(9), 1323–1341 (2012)

    Article  Google Scholar 

  4. Foroughi, P., et al.: Ultrasound bone segmentation using dynamic programming. In: Yuhas, M.P. (ed.) IEEE ultrasonics symposium on 2007, pp. 2523–2526 (2007)

    Google Scholar 

  5. Gao, Y., et al.: A 3D interactive multi-object segmentation tool using local robust statistics driven active contours. Med. Image Anal. 16(6), 1216–1227 (2012)

    Article  Google Scholar 

  6. Gill, S., et al.: Biomechanically constrained groupwise ultrasound to CT registration of the lumbar spine. Med. Image Anal. 16(3), 662–674 (2012)

    Article  Google Scholar 

  7. Jain, A.K., et al.: Understanding bone responses in B-mode ultrasound images and automatic bone surface extraction using a bayesian probabilistic framework. In: Walker, W.F., Emelianov, S.Y. (eds.) Medical Imaging 2004: Ultrasonic Imaging and Signal Processing, Proceedings of SPIE, vol. 5373, pp. 131–14 (2004)

    Google Scholar 

  8. Lang, A., et al.: Multi-modal registration of speckle-tracked freehand 3D ultrasound to CT in the lumbar spine. Med. Image Anal. 16(3), 675–686 (2012)

    Article  Google Scholar 

  9. Rasoulian, A., et al.: Feature-based multibody rigid registration of CT and ultrasound images of lumbar spine. Med. Phys. 39(6), 3154–3166 (2012)

    Article  Google Scholar 

  10. Reinertsen, I., et al.: Validation of vessel-based registration for correction of brain shift. Med. Image Anal. 11(4), 374–388 (2007)

    Article  Google Scholar 

  11. Solberg, O.V., et al.: 3D ultrasound reconstruction algorithms from analog and digital data. Ultrasonics 51(4), 405–419 (2011)

    Article  MathSciNet  Google Scholar 

  12. Tjardes, T., et al.: Image-guided spine surgery: state of the art and future directions. Eur Spine J 19(1), 25–45 (2010)

    Article  Google Scholar 

  13. Tran, D., et al.: Automatic Detection of Lumbar Anatomy in Ultrasound Images of Human Subjects. IEEE Trans Biomed Eng 57(9), 2248–2256 (2010)

    Article  Google Scholar 

  14. Winter, S., et al.: Registration of CT and intraoperative 3-D ultrasound images of the spine using evolutionary and gradient-based methods. IEEE Trans. Evol. Comput. 12(3), 284–296 (2008)

    Article  Google Scholar 

  15. Yan, C.X.B., et al.: Ultrasound-CT registration of vertebrae without reconstruction. Int. J. Comput. Assist. Radiol. Surg. 7(6), 901–909 (2012)

    Article  Google Scholar 

  16. Yushkevich, P.A., et al.: User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31(3), 1116–1128 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

The work was funded through the user-driven research-based innovation project VIRTUS (The Research Council of Norway Grant No. 219326, SonoWand AS) and through a PhD grant from the Liaison Committee between the Central Norway Regional Health Authority (RHA) and the Norwegian University of Science and Technology.

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Authors and Affiliations

  1. Department of Medical Technology, SINTEF Technology and Society, Trondheim, Norway

    Lars Eirik Bø, Tormod Selbekk & Ingerid Reinertsen

  2. Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway

    Lars Eirik Bø & Ingerid Reinertsen

  3. The Central Norway Regional Health Authority, Trondheim, Norway

    Lars Eirik Bø

  4. The Intervention Centre, Oslo University Hospital, Oslo, Norway

    Rafael Palomar

Authors
  1. Lars Eirik Bø
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  2. Rafael Palomar
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  3. Tormod Selbekk
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  4. Ingerid Reinertsen
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Corresponding author

Correspondence to Lars Eirik Bø .

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Editors and Affiliations

  1. Center Drive, National Institutes of Health, Bethesda, Massachusetts, USA

    Jianhua Yao

  2. Innovative Technologies Research Laboratories, Philips Research, Hamburg, Germany

    Tobias Klinder

  3. GE Healthcare and University of Western Ontario, London, Ontario, Canada

    Shuo Li

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© 2014 Springer International Publishing Switzerland

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Bø, L.E., Palomar, R., Selbekk, T., Reinertsen, I. (2014). Registration of MR to Percutaneous Ultrasound of the Spine for Image-Guided Surgery. In: Yao, J., Klinder, T., Li, S. (eds) Computational Methods and Clinical Applications for Spine Imaging. Lecture Notes in Computational Vision and Biomechanics, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-07269-2_18

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  • DOI: https://doi.org/10.1007/978-3-319-07269-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07268-5

  • Online ISBN: 978-3-319-07269-2

  • eBook Packages: EngineeringEngineering (R0)

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