Abstract
Endovascular image guided interventions involve catheter navigation through the vasculature to the treatment site under guidance of live 2D projection images. During treatment materials are delivered through the catheter that requires information about the blood flow direction, obtained by injecting contrast agent and observing its propagation on the live 2D images. To facilitate navigation and treatment the information from the live 2D images can be superimposed on a 3D vessel tree model, extracted from pre-interventional 3D images. However, the 3D and live 2D images first need to be spatially corresponded by a 3D-2D registration. In this paper, we propose a novel 3D-2D registration method based on matching orientations of 3D vessels’ centerlines to the edges of live 2D images. Results indicate that the proposed 3D-2D registration is highly robust and feasible for real-time execution (<1 s). Example of 3D contrast flow visualization also demonstrates the potential for real clinical application.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Rudin, S., Bednarek, D.R., Hoffmann, K.R.: Endovascular image-guided interventions (EIGIs). Med. Phys. 35, 301 (2008)
Ruijters, D., Homan, R., Mielekamp, P., van de Haar, P., Babic, D.: Validation of 3D multimodality roadmapping in interventional neuroradiology. Phys. Med. Biol. 56, 5335–5354 (2011)
Hipwell, J.H., et al.: Intensity-based 2-D - 3-D registration of cerebral angiograms. IEEE T. Med. Imaging 22, 1417–1426 (2003)
McLaughlin, R.A., Hipwell, J., Hawkes, D.J., Noble, J.A., Byrne, J.V., Cox, T.C.: A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use. IEEE T. Med. Imaging 24, 1058–1066 (2005)
Lee, T., Kashyap, R., Chu, C.: Building skeleton models via 3-D medial surface/axis thinning algorithms. CVGIP-Graph Model Im. 56, 462–478 (1994)
Krissian, K., Malandain, G., Ayache, N., Vaillant, R., Trousset, Y.: Model-Based Detection of Tubular Structures in 3D Images. Comput. Vis. Image Und. 80, 130–171 (2000)
Jomier, J., Bullitt, E., Van Horn, M., Pathak, C., Aylward, S.R.: 3D/2D model-to-image registration applied to TIPS surgery. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 662–669. Springer, Heidelberg (2006)
Kita, Y., Wilson, D.L., Noble, J.A.: Real-time registration of 3D cerebral vessels to X-ray angiograms. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 1125–1133. Springer, Heidelberg (1998)
Groher, M., Zikic, D., Navab, N.: Deformable 2D-3D registration of vascular structures in a one view scenario. IEEE T. Med. Imaging 28, 847–860 (2009)
Lewis, J.P.: Fast Normalized Cross-Correlation. In: Proceedings of Vision Interface, vol. 1995, pp. 120–123 (1995)
van de Kraats, E., Penney, G., Tomaževič, D., van Walsum, T., Niessen, W.: Standardized evaluation methodology for 2-D-3-D registration. IEEE T. Med. Imaging 24, 1177–1189 (2005)
Schmitt, H., Grass, M., Rasche, V., Schramm, O., Haehnel, S., Sartor, K.: An X-ray-based method for the determination of the contrast agent propagation in 3-D vessel structures. IEEE T. Med. Imaging 21, 251–262 (2002)
Weiler, F., Rieder, C., David, C.A., Wald, C., Hahn, H.K.: AVM-Explorer: Multi-Volume Visualization of Vascular Structures for Planning of Cerebral AVM Surgery. Spring Eurograp. 6, 2–5 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mitrović, U., Špiclin, Ž., Likar, B., Pernuš, F. (2013). Method for 3D-2D Registration of Vascular Images: Application to 3D Contrast Agent Flow Visualization. In: Drechsler, K., et al. Clinical Image-Based Procedures. From Planning to Intervention. CLIP 2012. Lecture Notes in Computer Science, vol 7761. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38079-2_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-38079-2_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38078-5
Online ISBN: 978-3-642-38079-2
eBook Packages: Computer ScienceComputer Science (R0)