Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2016, Article ID 4382854, 19 pages
http://dx.doi.org/10.1155/2016/4382854
Research Article

3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

1University of Texas at Dallas, Richardson, TX 75080, USA
2University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
3University of New Mexico, Albuquerque, NM 87131, USA

Received 11 September 2015; Accepted 28 December 2015

Academic Editor: Cristiana Corsi

Copyright © 2016 Zichun Zhong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Y. Long, J. A. Fessler, and J. M. Balter, “Accuracy estimation for projection-to-volume targeting during rotational therapy: a feasibility study,” Medical Physics, vol. 37, no. 6, pp. 2480–2490, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. R. S. Brock, A. Docef, and M. J. Murphy, “Reconstruction of a cone-beam CT image via forward iterative projection matching,” Medical Physics, vol. 37, no. 12, pp. 6212–6220, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Wang and X. Gu, “High-quality four-dimensional cone-beam CT by deforming prior images,” Physics in Medicine and Biology, vol. 58, no. 2, pp. 231–246, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Ren, I. J. Chetty, J. Zhang et al., “Development and clinical evaluation of a three-dimensional cone-beam computed tomography estimation method using a deformation field map,” International Journal of Radiation Oncology Biology Physics, vol. 82, no. 5, pp. 1584–1593, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. G. P. Penney, J. Weese, J. A. Little, P. Desmedt, D. L. G. Hill, and D. J. Hawkes, “A comparison of similarity measures for use in 2D-3D medical image registration,” IEEE Transactions on Medical Imaging, vol. 17, no. 4, pp. 586–595, 1998. View at Publisher · View at Google Scholar · View at Scopus
  6. J. Kim, F.-F. Yin, Y. Zhao, and J. H. Kim, “Effects of x-ray and CT image enhancements on the robustness and accuracy of a rigid 3D/2D image registration,” Medical Physics, vol. 32, no. 4, pp. 866–873, 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. R. Munbodh, H. D. Tagare, Z. Chen et al., “2D-3D registration for prostate radiation therapy based on a statistical model of transmission images,” Medical Physics, vol. 36, no. 10, pp. 4555–4568, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. J. Kybic and M. Unser, “Fast parametric elastic image registration,” IEEE Transactions on Image Processing, vol. 12, no. 11, pp. 1427–1442, 2003. View at Publisher · View at Google Scholar · View at Scopus
  9. A. Docef, M. Murphy, P. Keall, J. Siebers, and J. Williamson, “Forward CT reconstruction from limited projection data,” in Proceedings of the 19th Conference on Computer-Assisted Radiology and Surgery, pp. 104–108, June 2005.
  10. R. Zeng, J. A. Fesslr, and J. M. Balter, “Estimating 3-D respiratory motion from orbiting views by tomographic image registration,” IEEE Transactions on Medical Imaging, vol. 26, no. 2, pp. 153–163, 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. X. Jia, B. Dong, Y. Lou, and S. B. Jiang, “GPU-based iterative cone-beam CT reconstruction using tight frame regularization,” Physics in Medicine and Biology, vol. 56, no. 13, pp. 3787–3807, 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. M. Ferrant, S. K. Warfield, A. Nabavi, F. A. Jolesz, R. Kikinis, and B. Macq, “Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model,” IEEE Transactions on Medical Imaging, vol. 20, no. 12, pp. 1384–1397, 2001. View at Google Scholar
  13. O. Clatz, H. Delingette, I.-F. Talos et al., “Robust nonrigid registration to capture brain shift from intraoperative MRI,” IEEE Transactions on Medical Imaging, vol. 24, no. 11, pp. 1417–1427, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. B. Ahn and J. Kim, “Measurement and characterization of soft tissue behavior with surface deformation and force response under large deformations,” Medical Image Analysis, vol. 14, no. 2, pp. 138–148, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Hu, T. J. Carter, H. U. Ahmed et al., “Modelling prostate motion for data fusion during image-guided interventions,” IEEE Transactions on Medical Imaging, vol. 30, no. 11, pp. 1887–1900, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. P. Foteinos, Y. Liu, A. Chernikov, and N. Chrisochoides, “An evaluation of tetrahedral mesh generation for nonrigid registration of brain MRI,” in Computational Biomechanics for Medicine, pp. 131–142, Springer, 2011. View at Publisher · View at Google Scholar
  17. E. Haber, S. Heldmann, and J. Modersitzki, “Adaptive mesh refinement for nonparametric image registration,” SIAM Journal on Scientific Computing, vol. 30, no. 6, pp. 3012–3027, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  18. M. Fogtmann and R. Larsen, “Adaptive mesh generation for image registration and segmentation,” in Proceedings of the 20th IEEE International Conference on Image Processing (ICIP '13), pp. 757–760, IEEE, Melbourne, Australia, September 2013. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Zhang, J. Wang, X. Wang, and D. Feng, “The adaptive FEM elastic model for medical image registration,” Physics in Medicine and Biology, vol. 59, no. 1, pp. 97–118, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. J. G. Brankov, Y. Yang, and M. N. Wernick, “Content-adaptive 3D mesh modeling for representation of volumetric images,” in Proceedings of the International Conference on Image Processing, vol. 3, pp. 849–852, IEEE, June 2002. View at Publisher · View at Google Scholar
  21. J. G. Brankov, Y. Yang, and M. N. Wernick, “Tomographic image reconstruction based on a content-adaptive mesh model,” IEEE Transactions on Medical Imaging, vol. 23, no. 2, pp. 202–212, 2004. View at Publisher · View at Google Scholar · View at Scopus
  22. W.-S. V. Shih, W.-C. Lin, and C.-T. Chen, “Contour-model-guided nonlinear deformation model for intersubject image registration,” in Medical Imaging: Image Processing, vol. 3034 of Proceedings of SPIE, pp. 611–620, International Society for Optical Engineering, Newport Beach, Calif, USA, February 1997. View at Publisher · View at Google Scholar
  23. W.-N. Lie and C.-H. Chuang, “Contour-based image registration with local deformations,” Optical Engineering, vol. 42, no. 5, pp. 1405–1416, 2003. View at Publisher · View at Google Scholar · View at Scopus
  24. X. Gu, B. Dong, J. Wang et al., “A contour-guided deformable image registration algorithm for adaptive radiotherapy,” Physics in Medicine and Biology, vol. 58, no. 6, pp. 1889–1901, 2013. View at Publisher · View at Google Scholar · View at Scopus
  25. Z. Zhong, X. Guo, W. Wang et al., “Particle-based anisotropic surface meshing,” ACM Transactions on Graphics (TOG): SIGGRAPH 2013 Conference Proceedings, vol. 32, no. 4, article 99, 2013. View at Publisher · View at Google Scholar
  26. J. Nash, “C1-isometric imbeddings,” Annals of Mathematics, vol. 60, pp. 383–396, 1954. View at Publisher · View at Google Scholar · View at MathSciNet
  27. N. H. Kuiper, “On C1-isometric embeddings I,” Proceedings of the Koninklijke Nederlandse Akademie vanWetenschappen Series A, vol. 58, pp. 545–556, 1955. View at Google Scholar
  28. M. do Carmo, Riemannian Geometry, Birkhäauser, 1992. View at Publisher · View at Google Scholar · View at MathSciNet
  29. M. de Berg, O. Cheong, M. van Kreveld, and M. Overmars, Computational Geometry: Algorithms and Applications, Springer, New York, NY, USA, 2008. View at Publisher · View at Google Scholar
  30. D. C. Liu and J. Nocedal, “On the limited memory BFGS method for large scale optimization,” Mathematical Programming, vol. 45, no. 3, pp. 503–528, 1989. View at Publisher · View at Google Scholar · View at MathSciNet
  31. W. P. Segars and B. M. W. Tsui, “MCAT to XCAT: the evolution of 4-D computerized phantoms for imaging research,” Proceedings of the IEEE, vol. 97, no. 12, pp. 1954–1968, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. H. Coxeter, Introduction to Geometry, John Wiley & Sons, 2nd edition, 1969. View at MathSciNet
  33. R. L. Siddon, “Fast calculation of the exact radiological path for a three-dimensional CT array,” Medical Physics, vol. 12, no. 2, pp. 252–255, 1985. View at Publisher · View at Google Scholar · View at Scopus
  34. J. Wang, T. Li, H. Lu, and Z. Liang, “Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography,” IEEE Transactions on Medical Imaging, vol. 25, no. 10, pp. 1272–1283, 2006. View at Publisher · View at Google Scholar · View at Scopus
  35. P. J. La Rivière and D. M. Billmire, “Reduction of noise-induced streak artifacts in X-ray computed tomography through spline-based penalized-likelihood sinogram smoothing,” IEEE Transactions on Medical Imaging, vol. 24, no. 1, pp. 105–111, 2005. View at Publisher · View at Google Scholar · View at Scopus
  36. K. Zhou, J. Huang, J. Snyder et al., “Large mesh deformation using the volumetric graph laplacian,” ACM Transactions on Graphics, vol. 24, no. 3, pp. 496–503, 2005. View at Publisher · View at Google Scholar
  37. J. Canny, “A computational approach to edge detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679–698, 1986. View at Publisher · View at Google Scholar
  38. L. Westover, “Footprint evaluation for volume rendering,” in Proceedings of the 17th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '90), pp. 367–376, ACM, Dallas, Tex, USA, August 1990. View at Publisher · View at Google Scholar
  39. R. A. Hälg, J. Besserer, and U. Schneider, “Systematic measurements of whole-body imaging dose distributions in image-guided radiation therapy,” Medical Physics, vol. 39, no. 12, pp. 7650–7661, 2012. View at Publisher · View at Google Scholar · View at Scopus