Skip to main content

Particle Swarm Optimization for In Vivo 3D Ultrasound Volume Registration

  • Conference paper
  • First Online:
  • 1241 Accesses

Part of the book series: Acoustical Imaging ((ACIM,volume 30))

Abstract

As three-dimensional (3D) ultrasound is becoming more and more popular, there has been increased interest in using a position sensor to track the trajectory of the 3D ultrasound probe during the scan. One application is the improvement of image quality by fusion of multiple scans from different orientations. With a position sensor mounted on the probe, the clinicians face additional difficulties, for example, maintaining a line-of-sight between the sensor and the reference point. Therefore, the objective of this paper is to register the volumes using an automatic image-based registration technique. In this paper, we employ the particle swarm optimization (PSO) technique to calculate the six rigid-body transformation parameters (three for translation and three for rotation) between successive volumes of 3D ultrasound data. We obtain vertical and horizontal slices through the acquired volumes and then use an intensity-based similarity measure as a fitness function for each particle. We considered various settings in the PSO to find a set of parameters to give the best convergence. We found the visually acceptable registration when the initial orientations of the particles were confined to within a few degrees of the orientations obtained from position sensor.

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   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Chang, C.–Y., Lai, C.–T., Chen, S.–J.: Applying the particle swarm optimization and Boltzmann function for feature selection and classification of lymph node in ultrasound images. In: Proceedings of the 2008 Eighth International Conference on Intelligent System Design and Applications, pp. 55–60 (2008)

    Google Scholar 

  2. Guo, Y., Cheng, H.D., Tian, J., Zhang, Y.: A novel approach to breast ultrasound image segmentation based on the characteristics of breast tissue and particle swarm optimization. In: Proceedings of the 11th Joint Conference on Information Science (2008)

    Google Scholar 

  3. Wachowiak, M.P., Smolíková, R., Zheng, Y., Zurada, J.M., Elmaghraby, A.S.: An approach to multimodal biomedical image registration utilizing particle swarm optimization. IEEE Trans. Evol. Comput. 8(3), 289–301 (2004)

    Article  Google Scholar 

  4. Trelea, I.C.: The particle swarm optimization algorithm: convergence analysis and parameter selection. Information Process. Lett. 85, 317–325 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  5. Zhang, Z.: Estimating mutual information via Kolmogorov distance. IEEE Trans. Inform. Theor. 53(9), 3280–3282 (2007)

    Article  Google Scholar 

  6. Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)

    Google Scholar 

  7. Treece, G.M., Prager, R.W., Gee, A.H., Berman, L.: Correction of probe pressure artifacts in freehand 3D ultrasound. Medical Image Analysis 6(3), 199–214 (2002)

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/F016476/1.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to U. Z. Ijaz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media B.V.

About this paper

Cite this paper

Ijaz, U.Z., Prager, R., Gee, A., Treece, G. (2011). Particle Swarm Optimization for In Vivo 3D Ultrasound Volume Registration. In: André, M., Jones, J., Lee, H. (eds) Acoustical Imaging. Acoustical Imaging, vol 30. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3255-3_39

Download citation

Publish with us

Policies and ethics