Skip to main content

An Efficient Registration Algorithm for Advanced Fusion of 2D/3D Angiographic Data

  • Conference paper
Bildverarbeitung für die Medizin 2007

Part of the book series: Informatik aktuell ((INFORMAT))

Abstract

Computed tomography angiography (CTA) is often used for pre-interventional diagnosis and planning, whereas nowadays, mostly 2D angiograms are acquired for intra-interventional catheter guidance. Spatial information from pre-interventional scans is not transferred to the intervention yet since existing 2D-3D registration methods either require a good initial manual alignment or have rather long runtime and thus lack clinical usefulness. We propose a fast and automatic method for 2D-3D registration and evaluate methods for intra-interventional visualization and navigation. Moreover, we introduce an easy clinical work- flow for transferring a planned roadmap from pre-interventional 3D to intra-interventional 2D using the registration. We demonstrate the good quality of fit and the fast runtime of the algorithm on one phantom and three patient data sets.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Groher M, Padoy N, Jakobs TF, Navab N. New CTA protocol and 2D-3D registration method for liver catheterization. LNCS 2006;4190:873–881.

    Google Scholar 

  2. Jomier J, Bullitt E, v Horn M, Pathak C, Aylward SR. 3D/2D model-to-image registration applied to TIPS surgery. LNCS 2006;4191:662–669.

    Google Scholar 

  3. Florin C, Williams J, Khamene A, Paragios N. Registration of 3D angiographic and x-ray images using sequential monte Carlo Sampling. LNCS 2005;3765:427–436.

    Google Scholar 

  4. Turgeon GA, Lehmann G, Guiraudon G, et al. 2D-3D registration of coronary angiograms for cardiac procedure planning and guidance. Med Phys 2005;32:3737–3749.

    Article  Google Scholar 

  5. Zahlten C, Jürgens H, Peitgen HO. Reconstruction of branching blood vessels from CT-data. In: Eurographics Workshop of Visualization in Scientific Computing. Springer; 1994. 161–168.

    Google Scholar 

  6. Belongie S, Malik J, Puzicha J. Shape matching and object recognition using shape contexts. IEEE Trans PAMI 2002;24:509–522.

    Google Scholar 

  7. Tory M. Mental registration of 2D and 3D visualizations: An empirical study. In: Procs IEEE Visualization Conference. Seattle, Washington, USA; 2003. 49.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Groher, M., Hoffmann, RT., Zech, C., Reiser, M., Navab, N. (2007). An Efficient Registration Algorithm for Advanced Fusion of 2D/3D Angiographic Data. In: Horsch, A., Deserno, T.M., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2007. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71091-2_32

Download citation

Publish with us

Policies and ethics