Skip to main content

Registration of Pre-Operative CT and Non-Contrast-Enhanced C-Arm CT: An Application to Trans-Catheter Aortic Valve Implantation (TAVI)

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7725))

Abstract

Trans-catheter Aortic Valve Implantation (TAVI) has proven to be an effective minimal-invasive alternative to traditional open-heart valve replacement surgery. Despite the success of contrast enhanced C-arm CT for intra-operative guidance during TAVI, utilization of pre-operative CT in the Hybrid Operating Room provides additional advantages of an improved workflow and minimized usage of contrast agent. In this paper, we propose a framework for CT/non-contrast-enhanced C-arm CT volume registration so that pre-operative CT can be used intra-operatively without additional contrast medium. The proposed method consists of two steps, rigid-body coarse alignment followed by deformable fine registration. Our contribution is twofold. First, robust heart center detection on both image modalities is used to boost the success rate of rigid-body registration. Second, a structural encoded similarity measure and anatomical correlation-regularized deformation fields are proposed to improve the performance of intensity-based deformable registration using the variational framework. Experiments were performed on ten sets of TAVI patient data, and the results have shown that the proposed method provides a highly robust and accurate registration. The resulting accuracy of 1.83 mm mean mesh-to-mesh error at the aortic root and the high efficiency of an average running time of 2 minutes on a common computer make it potentially feasible for clinical usage in TAVI. The proposed heart registration method is generic and hence can be easily applied to other cardiac applications.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Nkomo, V., Gardin, J., Skelton, T., Gottdiener, J., Scott, C., Enriquez-Sarano, M.: Burden of valvular heart diseases: a population-based study. The Lancet 368, 1005–1011 (2006)

    Article  Google Scholar 

  2. John, M., Liao, R., Zheng, Y., Nöttling, A., Boese, J., Kirschstein, U., Kempfert, J., Walther, T.: System to Guide Transcatheter Aortic Valve Implantations Based on Interventional C-Arm CT Imaging. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part I. LNCS, vol. 6361, pp. 375–382. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  3. Krishnaswamy, A., Tuzcu, E., Kapadia, S.: Three-dimensional computed tomography in the cardiac catheterization laboratory. Catheterization and Cardiovascular Interventions 77, 860–865 (2011)

    Article  Google Scholar 

  4. Grbić, S., Ionasec, R., Wang, Y., Mansi, T., Georgescu, B., John, M., Boese, J., Zheng, Y., Navab, N., Comaniciu, D.: Model-Based Fusion of Multi-modal Volumetric Images: Application to Transcatheter Valve Procedures. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part I. LNCS, vol. 6891, pp. 219–226. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Andronache, A., Von Siebenthal, M., Székely, G., Cattin, P.: Non-rigid registration of multi-modal images using both mutual information and cross-correlation. MIA 12, 3–15 (2008)

    Google Scholar 

  6. Kyriacou, S., Davatzikos, C., Zinreich, S., Bryan, R.: Nonlinear elastic registration of brain images with tumor pathology using a biomechanical model MRI. IEEE TMI 18, 580–592 (1999)

    Google Scholar 

  7. Stefanescu, R., Commowick, O., Malandain, G., Bondiau, P.-Y., Ayache, N., Pennec, X.: Non-rigid Atlas to Subject Registration with Pathologies for Conformal Brain Radiotherapy. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 704–711. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Hermosillo, G., Chefd’Hotel, C., Faugeras, O.: Variational methods for multimodal image matching. IJCV 50, 329–343 (2002)

    Article  MATH  Google Scholar 

  9. Lorenz, C., von Berg, J.: Fast automated object detection by recursive casting of search rays. International Congress Series, vol. 1281, pp. 230–235. Elsevier (2005)

    Google Scholar 

  10. Pluim, J., Maintz, J., Viergever, M.: Mutual-information-based registration of medical images: a survey. IEEE TMI 22, 986–1004 (2003)

    Google Scholar 

  11. Zhuang, X., Arridge, S., Hawkes, D., Ourselin, S.: A nonrigid registration framework using spatially encoded mutual information and free-form deformations. IEEE Transactions on Medical Imaging 30, 1819–1828 (2011)

    Article  Google Scholar 

  12. Gan, R., Chung, A.C.S.: Multi-dimensional Mutual Information Based Robust Image Registration Using Maximum Distance-Gradient-Magnitude. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 210–221. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  13. Suh, J., Scheinost, D., Qian, X., Sinusas, A., Breuer, C., Papademetris, X.: Serial nonrigid vascular registration using weighted normalized mutual information. In: 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 25–28. IEEE (2010)

    Google Scholar 

  14. Wang, J., Li, F., Li, Q.: Automated segmentation of lungs with severe interstitial lung disease in ct. Medical physics 36, 4592 (2009)

    Article  Google Scholar 

  15. Miao, S., Liao, R., Pfister, M.: Toward smart utilization of two x-ray images for 2-d/3-d registration applied to abdominal aortic aneurysm interventions. In: 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), vol. 1, pp. 550–555. IEEE (2011)

    Google Scholar 

  16. Chefd’hotel, C., Hermosillo, G., Faugeras, O.: Flows of diffeomorphisms for multimodal image registration. In: Proceedings of the IEEE International Symposium on Biomedical Imaging, pp. 753–756. IEEE (2002)

    Google Scholar 

  17. Murphy, K., Van Ginneken, B., Reinhardt, J., Kabus, S., Ding, K., Deng, X., Cao, K., Du, K., Christensen, G., Garcia, V., et al.: Evaluation of registration methods on thoracic ct: The empire10 challenge. IEEE TMI 30, 1901 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lu, Y., Sun, Y., Liao, R., Ong, S.H. (2013). Registration of Pre-Operative CT and Non-Contrast-Enhanced C-Arm CT: An Application to Trans-Catheter Aortic Valve Implantation (TAVI). In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37444-9_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37444-9_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37443-2

  • Online ISBN: 978-3-642-37444-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics