2D/3D Catheter-Based Registration for Image Guidance in TACE of Liver Tumors

  • Pierre Ambrosini
  • Danny Ruijters
  • Adriaan Moelker
  • Wiro J. Niessen
  • Theo van Walsum
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8498)


Image fusion of liver 2D X-ray images and pre or peri-operative 3D reconstructions can add valuable contextual information during image guided interventions. Such image fusion requires 2D/3D registration. In abdominal interventions, such as TACE of liver tumors, the initial alignment may be invalidated by e.g. breathing motion. We present a method that maintains the alignment between 3D Rotational Angiography (3DRA) and 2D X-ray, using the catheter position. To this end, we use the catheter in the 2D X-ray and the blood vessels in the 3DRA, then fuse 2D/3D using the knowledge that the catheter is inside the vessels. The registration is performed in two steps: First, we use a shape constraint to determine the most likely catheter positions inside the blood vessel tree. Next, we perform a rigid registration and take the best transformation over all previous selected catheter positions. The method is evaluated on phantom, clinical and simulated data.


2D/3D Rigid Catheter Registration Guidance X-ray Fluoroscopy 3DRA Abdominal TACE Liver Breathing Compensation. 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Groher, M., Zikic, D., Navab, N.: Deformable 2D-3D registration of vascular structures in a one view scenario. IEEE Transactions on Medical Imaging 28(6), 847–860 (2009)CrossRefGoogle Scholar
  2. 2.
    Rivest-Henault, D., Sundar, H., Cheriet, M.: Nonrigid 2D/3D registration of coronary artery models with live fluoroscopy for guidance of cardiac interventions. IEEE Transactions on Medical Imaging 31(8), 1557–1572 (2012)CrossRefGoogle Scholar
  3. 3.
    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)CrossRefGoogle Scholar
  4. 4.
    Ma, Y., King, A., Gogin, N., Gijsbers, G., Rinaldi, C., Gill, J., Razavi, R., Rhode, K.: Clinical evaluation of respiratory motion compensation for anatomical roadmap guided cardiac electrophysiology procedures. IEEE Transactions on Biomedical Engineering 59(1), 122–131 (2012)CrossRefGoogle Scholar
  5. 5.
    Metz, C., et al.: Alignment of 4d coronary cta with monoplane x-ray angiography. In: Linte, C.A., Moore, J.T., Chen, E.C.S., Holmes III, D.R., et al. (eds.) AE-CAI 2011. LNCS, vol. 7264, pp. 106–116. Springer, Heidelberg (2012)Google Scholar
  6. 6.
    Ruijters, D., Homan, R., Mielekamp, P., van de Haar, P., Babic, D.: Validation of 3d multimodality roadmapping in interventional neuroradiology. Physics in Medicine and Biology 56(16), 5335–5354 (2011)CrossRefGoogle Scholar
  7. 7.
    Markelj, P., Tomaževič, D., Likar, B., Pernuš, F.: A review of 3D/2D registration methods for image-guided interventions. Medical Image Analysis 16(3), 642–661 (2012)CrossRefGoogle Scholar
  8. 8.
    Liao, R., Zhang, L., Sun, Y., Miao, S., Chefd’hotel, C.: A review of recent advances in registration techniques applied to minimally invasive therapy. IEEE Transactions on Multimedia 15(5), 983–1000 (2013)CrossRefGoogle Scholar
  9. 9.
    Atasoy, S., Groher, M., Zikic, D., Glocker, B., Waggershauser, T., Pfister, M., Navab, N.: Real-time respiratory motion tracking: roadmap correction for hepatic artery catheterizations. In: Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-guided Procedures, and Modeling, p. 691815 (March 20, 2008)Google Scholar
  10. 10.
    Heibel, H., Glocker, B., Groher, M., Pfister, M., Navab, N.: Interventional tool tracking using discrete optimization. IEEE Transactions on Medical Imaging 32(3), 544–555 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Pierre Ambrosini
    • 1
  • Danny Ruijters
    • 2
  • Adriaan Moelker
    • 3
  • Wiro J. Niessen
    • 1
    • 4
  • Theo van Walsum
    • 1
  1. 1.Biomedical Imaging Group Rotterdam, Department of Radiology and Medical Informatics, Erasmus MCRotterdamThe Netherlands
  2. 2.Philips Healthcare, Interventional X-ray Innovation, BestThe Netherlands
  3. 3.Department of Radiology, Erasmus MCRotterdamThe Netherlands
  4. 4.Imaging Science and Technology, Faculty of Applied SciencesDelft University of TechnologyDelftThe Netherlands

Personalised recommendations