Skip to main content

Advertisement

SpringerLink
Log in
Menu
Find a journal Publish with us
Search
Cart
Book cover

International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2012: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012 pp 66–73Cite as

  1. Home
  2. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012
  3. Conference paper
Automated Skeleton Based Multi-modal Deformable Registration of Head&Neck Datasets

Automated Skeleton Based Multi-modal Deformable Registration of Head&Neck Datasets

  • Sebastian Steger19 &
  • Stefan Wesarg19 
  • Conference paper
  • 4023 Accesses

  • 5 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7511)

Abstract

This paper presents a novel skeleton based method for the registration of head&neck datasets. Unlike existing approaches it is fully automated, spatial relation of the bones is considered during their registration and only one of the images must be a CT scan. An articulated atlas is used to jointly obtain a segmentation of the skull, the mandible and the vertebrae C1-Th2 from the CT image. These bones are then successively rigidly registered with the moving image, beginning at the skull, resulting in a rigid transformation for each of the bones. Linear combinations of those transformations describe the deformation in the soft tissue. The weights for the transformations are given by the solution of the Laplace equation. Optionally, the skin surface can be incorporated. The approach is evaluated on 20 CT/MRI pairs of head&neck datasets acquired in clinical routine. Visual inspection shows that the segmentation of the bones was successful in all cases and their successive alignment was successful in 19 cases. Based on manual segmentations of lymph nodes in both modalities, the registration accuracy in the soft tissue was assessed. The mean target registration error of the lymph node centroids was 5.33 ± 2.44 mm when the registration was solely based on the deformation of the skeleton and 5.00 ± 2.38 mm when the skin surface was additionally considered. The method’s capture range is sufficient to cope with strongly deformed images and it can be modified to support other parts of the body. The overall registration process typically takes less than 2 minutes.

Keywords

  • Image Registration
  • Head&Neck
  • Multi-Modal
  • Multi-Rigid

Download conference paper PDF

References

  1. Al-Mayah, A., et al.: Biomechanical-based image registration for head and neck radiation treatment. Phys. Med. Biol. 55(21), 6491 (2010)

    CrossRef  Google Scholar 

  2. Alexa, M.: Linear combination of transformations. In: SIGGRAPH 2002, pp. 380–387. ACM, New York (2002)

    CrossRef  Google Scholar 

  3. Arsigny, V., et al.: A fast and log-euclidean polyaffine framework for locally linear registration. J. Math Imaging Vis. 33, 222–238 (2009)

    CrossRef  MathSciNet  Google Scholar 

  4. Baiker, M., et al.: Fully automated whole-body registration in mice using an atriculated skeleton atlas. In: Proc IEEE Int. Symp. Biomed. Imaging, pp. 728–731 (2007)

    Google Scholar 

  5. du Bois dAische, A., et al.: Estimation of the deformations induced by articulated bodies: Registration of the spinal column. Biomed Signal Proces. 2(1), 16–24 (2007)

    CrossRef  Google Scholar 

  6. Hu, Y., Haynor, D.R.: Multirigid registration of mr and ct images of the cervical spine. In: Fitzpatrick, J.M., Sonka, M. (eds.) Medical Imaging 2004: Image Processing, vol. 5370, pp. 1527–1538. SPIE (2004)

    Google Scholar 

  7. Huesman, R., et al.: Deformable registration of multi-modal data including rigid structures. In: IEEE Nucl. Sci. Symp. Conf. Rec., vol. 3, pp. 1879–1882 (2002)

    Google Scholar 

  8. Li, X., Peterson, T.E., Gore, J.C., Dawant, B.M.: Automatic Inter-subject Registration of Whole Body Images. In: Pluim, J.P.W., Likar, B., Gerritsen, F.A. (eds.) WBIR 2006. LNCS, vol. 4057, pp. 18–25. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  9. Little, J., et al.: Deformations incorporating rigid structures. In: Proc. Math. Methods in Biomed. Image Anal., pp. 104–113 (June 1996)

    Google Scholar 

  10. Martín-Fernández, M.A., et al.: Automatic articulated registration of hand radiographs. Image Vision Comput. 27(8), 1207–1222 (2009)

    CrossRef  Google Scholar 

  11. Papademetris, X., Dione, D.P., Dobrucki, L.W., Staib, L.H., Sinusas, A.J.: Articulated Rigid Registration for Serial Lower-Limb Mouse Imaging. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 919–926. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  12. Steger, S., et al.: Articulated atlas for segmentation of the skeleton from head & neck ct datasets. In: Proc IEEE Int. Symp. Biomed. Imaging, pp. 1256–1259 (2012)

    Google Scholar 

  13. Suh, J.W., et al.: A non-rigid registration method for serial lower extremity hybrid spect/ct imaging. Med. Image Anal. 15(1), 96–111 (2011)

    CrossRef  Google Scholar 

  14. Čech, P., et al.: Piecewise rigid multimodal spine registration. In: Handels, H., Ehrhardt, J., Horsch, A., Meinzer, H.-P., Tolxdorff, T. (eds.) Bildverarbeitung für die Medizin 2006, pp. 211–215. Informatik aktuell, Springer, Heidelberg (2006)

    Google Scholar 

  15. Wang, K., He, Y., Qin, H.: Incorporating Rigid Structures in Non-rigid Registration Using Triangular B-Splines. In: Paragios, N., Faugeras, O., Chan, T., Schnörr, C. (eds.) VLSM 2005. LNCS, vol. 3752, pp. 235–246. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Cognitive Computing & Medical Imaging, Fraunhofer IGD, Darmstadt, Germany

    Sebastian Steger & Stefan Wesarg

Authors
  1. Sebastian Steger
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefan Wesarg
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Project Team Asclepios, Inria Sophia Antipolis, 06902, Sophia-Antipolis, France

    Nicholas Ayache & Hervé Delingette & 

  2. MIT, CSAIL, 02139, Cambridge, MA, USA

    Polina Golland

  3. Information and Communication Headquarters, Nagoya University, 464-8603, Nagoya, Japan

    Kensaku Mori

Rights and permissions

Reprints and Permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Steger, S., Wesarg, S. (2012). Automated Skeleton Based Multi-modal Deformable Registration of Head&Neck Datasets. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33418-4_9

Download citation

  • .RIS
  • .ENW
  • .BIB
  • DOI: https://doi.org/10.1007/978-3-642-33418-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33417-7

  • Online ISBN: 978-3-642-33418-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Search

Navigation

  • Find a journal
  • Publish with us

Discover content

  • Journals A-Z
  • Books A-Z

Publish with us

  • Publish your research
  • Open access publishing

Products and services

  • Our products
  • Librarians
  • Societies
  • Partners and advertisers

Our imprints

  • Springer
  • Nature Portfolio
  • BMC
  • Palgrave Macmillan
  • Apress
  • Your US state privacy rights
  • Accessibility statement
  • Terms and conditions
  • Privacy policy
  • Help and support

167.114.118.210

Not affiliated

Springer Nature

© 2023 Springer Nature