Skip to main content

Advertisement

Log in

Multiresolution Image Registration in Digital X-Ray Angiography with Intensity Variation Modeling

  • Research Article
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Digital subtraction angiography (DSA) is a widely used technique for visualization of vessel anatomy in diagnosis and treatment. However, due to unavoidable patient motions, both externally and internally, the subtracted angiography images often suffer from motion artifacts that adversely affect the quality of the medical diagnosis. To cope with this problem and improve the quality of DSA images, registration algorithms are often employed before subtraction. In this paper, a novel elastic registration algorithm for registration of digital X-ray angiography images, particularly for the coronary location, is proposed. This algorithm includes a multiresolution search strategy in which a global transformation is calculated iteratively based on local search in coarse and fine sub-image blocks. The local searches are accomplished in a differential multiscale framework which allows us to capture both large and small scale transformations. The local registration transformation also explicitly accounts for local variations in the image intensities which incorporated into our model as a change of local contrast and brightness. These local transformations are then smoothly interpolated using thin-plate spline interpolation function to obtain the global model. Experimental results with several clinical datasets demonstrate the effectiveness of our algorithm in motion artifact reduction.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Brody, W. R., Digital subtraction angiography. IEEE Trans. Nucl. Sci. 29(3):1176–1180, 1982.

    Article  MathSciNet  Google Scholar 

  2. Meijering, E. H. W., Zuiderveld, K. J., and Viergever, M. A., Image registration for digital subtraction angiography. Int. J. Comput. Vis. 31(2/3):227–246, 1999.

    Article  Google Scholar 

  3. Zitova, B., and Flusser, J., Image registration methods: A survey. Image Vis. Comput. 21(11):977–1000, 2003.

    Article  Google Scholar 

  4. Brown, L. G., A survey of image registration techniques. ACM Comput. Surv. 24(4):325–276, 1992.

    Article  Google Scholar 

  5. Elsen, V. D., Pol, P. A., and Viergever, E.-J. D., Medical image matching: A review with classification. IEEE Eng. Med. Biol. Magazine 12(1):26–39, 1993.

    Article  Google Scholar 

  6. Maintz, J. B. A., and Viergever, M. A., A survey of medical image registration. Med. Image Anal. 2(1):1–36, 1998.

    Article  Google Scholar 

  7. Hajnal, J. V., Hill, D. L. G., and Hawkes, D. J., Medical image registration. CRS Press, Baton Rouge, Florida, 2001.

    Book  Google Scholar 

  8. Cox, G. S., De Jager, G. “Automatic registration of temporal image pairs for digital subtraction angiography,” In: Loew M. H. (ed.), Proceedings of the SPIE, Medical imaging: image processing, vol. 2167, pp. 188–199, Bellingham, WA, 1994.

  9. Nejati, M., Sadri, S., and Amirfattahi, R., “Nonrigid Image Registration in Digital Subtraction Angiography Using Multilevel B-Spline”, BioMed Research International, pp. 1–12, vol. 2013.

  10. Buzug, T. M., Weese, J., Fassnacht, C., and Lorenz, C., Using an entropy similarity measure to enhance the quality of DSA images with an algorithm based on template matching. In: Höhne, K.-H., and Kikinis, R. (Eds.), VBC’96, Lecture Notes in Computer Science, vol. 1131. Springer, Berlin, pp. 235–240, 1996.

    Google Scholar 

  11. Buzug, T. M., Weese, J., Lorenz, C., and Beil, W., Histogram-based image registration for digital subtraction angiography. In: Del Bimbo, A. (Ed.), ICIAP’97, Lecture Notes in Computer Science, vol. 1311. Springer, Berlin, pp. 380–387, 1997.

    Google Scholar 

  12. Buzug, T. M., and Weese, J., Image registration for DSA quality enhancement. Comput. Med. Imaging Graph. 22(2):103–113, 1998.

    Article  Google Scholar 

  13. Cao, Z., Liu, X., Peng, B., Moon, Y.-S. “DSA image registration based on multiscale Gabor filters and mutual information”. In: Proceedings of the IEEE ICIA’05, Hong Kong and Macau, China, pp. 105–110, 2005.

  14. Taleb, N., and Jetto, L., Image registration for applications in digital subtraction angiography. Control. Eng. Pract. 6(2):227–238, 1998.

    Article  Google Scholar 

  15. Bentoutou, Y., Taleb, N., Chikr El Mezouar, M., Taleb, M., and Jetto, L., An invariant approach for image registration in digital subtraction angiography. Pattern Recogn. 35(12):2853–2865, 2002.

    Article  MATH  Google Scholar 

  16. Bentoutou, Y., and Taleb, N., Automatic extraction of control points for digital subtraction angiography image enhancement. IEEE Trans. Nucl. Sci. 52(1):238–246, 2005.

    Article  Google Scholar 

  17. Bentoutou, Y., and Taleb, N., A 3-D space-time motion detection for an invariant image registration approach in digital subtraction angiography. Comput. Vis. Image Underst. 97(1):30–50, 2005.

    Article  Google Scholar 

  18. Meijering, E. H. W., Niessen, W. J., and Viergever, M. A., Retrospective motion correction in digital subtraction angiography: a review. IEEE Trans. Med. Imaging 18(1):2–21, 1999.

    Article  Google Scholar 

  19. Ping, L., Hong, N., Ye, S. “An efficient method for image registration in DSA,” In: Proceedings of the ISISE’08, Shanghai, China, vol. 2, pp. 551–554, 2008.

  20. Nejati, M., Amirfattahi, R., Sadri, S.“A fast image registration algorithm for digital subtraction angiography”, In: Proceedings of 17th Iranian Conference of Biomedical Engineering (ICBME2010), Isfahan, Iran, pp. 1–4, November 2010.

  21. Chu, Y., Bai, N., Ji, Z., Chen, S., Mou, X. “Registration for DSA image using triangle grid and spatial transformation based on stretching”, In: Proceedings of the 8th International Conference on Signal Processing, Beijing, China, 16–20 Nov. 2006.

  22. Wang, J., Zhang, J. Q. “An iterative refinement DSA image registration algorithm using structural image quality measure”, In: Proceedings of the 5th IIH-MSP, Kyoto, Japan, pp. 973–976, 2009.

  23. Yang, J., Wang, Y., Tang, S., Zhou, S., Liu, Y., and Chen, W., Multiresolution elastic registration of X-ray angiography images using thin-plate spline. IEEE Trans. Nucl. Sci. 54(1):152–166, 2007.

    Article  Google Scholar 

  24. Nejati, M., Pourghassem, H. “Multiresolution search strategy for elastic registration of x-ray angiography images”, In Proceedings of International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI 2011), pp. 216–219, Wuhan, China, 14–17 Dec. 2011.

  25. Periaswamy, S., and Farid, H., Elastic registration in the Presence of Intensity Variations. IEEE Trans. Med. Imaging 22(7):865–874, 2003.

    Article  Google Scholar 

  26. Bookstein, F. L., Principal warps: thin-plate splines and the decomposition of deformations. IEEE Transact. Pattern Anal. Mach. Intell. 11(6):567–585, 1989.

    Article  MATH  Google Scholar 

  27. Farid, H., Simoncelli, E. P.“Optimally rotation-equivariant directional derivative kernels”, In Proceedings of International Conference on Computer Analysis of Images and Patterns, pp. 207–214, Berlin, Germany, Sept. 1997.

  28. Powell, M. J. D., An efficient method for finding the minimum of a function of several variables without calculating derivatives. Comput. J. 7(2):155–162, 1964.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dr. Hashemi of Sina Heart Hospital in Isfahan, Iran, for providing us the datasets used in the experiments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hossein Pourghassem.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nejati, M., Pourghassem, H. Multiresolution Image Registration in Digital X-Ray Angiography with Intensity Variation Modeling. J Med Syst 38, 10 (2014). https://doi.org/10.1007/s10916-014-0010-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10916-014-0010-8

Keywords

Navigation