Advertisement

Fast Mesh-Based Medical Image Registration

  • Ahmadreza Baghaie
  • Zeyun Yu
  • Roshan M. D’souza
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8888)

Abstract

In this paper a fast triangular mesh based registration method is proposed. Having Template and Reference images as inputs, the template image is triangulated using a content adaptive mesh generation algorithm. Considering the pixel values at mesh nodes, interpolated using spline interpolation method for both of the images, the energy functional needed for image registration is minimized. The minimization process was achieved using a mesh based discretization of the distance measure and regularization term which resulted in a sparse system of linear equations, which due to the smaller size in comparison to the pixel-wise registration method, can be solved directly. Mean Squared Difference (MSD) is used as a metric for evaluating the results. Using the mesh based technique, higher speed was achieved compared to pixel-based curvature registration technique with fast DCT solver. The implementation was done in MATLAB without any specific optimization. Higher speeds can be achieved using C/C++ implementations.

Keywords

Medical image registration triangular mesh generation content adaptive mesh generation diffusion process 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Patton, N., Aslam, T.M., MacGillivray, T., Deary, I.J., Dhillon, B., Eikelboom, R.H., Yogesan, K., Constable, I.J.: Retinal image analysis: concepts, applications and potential. Prog. Retin. Eye Res. 25(1), 99–127 (2006)CrossRefGoogle Scholar
  2. 2.
    Baghaie, A., Yu, Z.: Curvature-Based Registration for Slice Interpolation of Medical Images. In: Zhang, Y.J., Tavares, J.M.R.S. (eds.) CompIMAGE 2014. LNCS, vol. 8641, pp. 69–80. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  3. 3.
    Zitova, B., Flusser, J.: Image registration methods: a survey. Image Vision Comput. 21(11), 977–1000 (2003)CrossRefGoogle Scholar
  4. 4.
    Modersitzki, J.: Numerical methods for image registration. OUP, Oxford (2003)Google Scholar
  5. 5.
    Fischer, B., Modersitzki, J.: A unified approach to fast image registration and a new curvature based registration technique. Linear Algebra Appl. 380, 107–124 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  6. 6.
    Sotiras, A., Davatzikos, C., Paragios, N.: Deformable medical image registration: A survey. IEEE T. Med. Imaging 32(7), 1153–1190 (2013)CrossRefGoogle Scholar
  7. 7.
    Penney, G.P., Weese, J., Little, J.A., Desmedt, P., Hill, D.L.G., Hawkes, D.J.: A comparison of similarity measures for use in 2-D-3-D medical image registration. IEEE T. Med. Imaging 17(4), 586–595 (1998)CrossRefGoogle Scholar
  8. 8.
    Fluck, O., Vetter, C., Wein, W., Kamen, A., Preim, B., Westermann, R.: A survey of medical image registration on graphics hardware. Comput. Meth. Prog. Bio. 104(3), e45–e57 (2011)Google Scholar
  9. 9.
    Corvi, M., Nicchiotti, G.: Multiresolution image registration. In: EEE International Conference on Image Processing 1995, vol. 3, pp. 224–227. IEEE Press (1995)Google Scholar
  10. 10.
    Haber, E., Heldmann, S., Modersitzki, J.: Adaptive mesh refinement for nonparametric image registration. SIAM J. Sci. Comput. 30(6), 3012–3027 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  11. 11.
    Popuri, K., Cobzas, D., Jagersand, M.: Fast FEM-based non-rigid registration. In: Canadian Conference on Computer and Robot Vision (CRV) 2010. IEEE Press (2010)Google Scholar
  12. 12.
    Xu, M., Gao, Z., Yu, Z.: Feature-Sensitive and Adaptive Mesh Generation of Grayscale Images. In: Zhang, Y.J., Tavares, J.M.R.S. (eds.) CompIMAGE 2014. LNCS, vol. 8641, pp. 204–215. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  13. 13.
    Xu, G.: Convergent discrete Laplace-Beltrami operators over triangular surfaces. In: Geometric Modeling and Processing 2004. IEEE Press (2004)Google Scholar
  14. 14.
    Desbrun, M., Meyer, M., Schrder, P., Barr, A.H.: Implicit fairing of irregular meshes using diffusion and curvature flow. In: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques, pp. 317–324. ACM Press/Addison-Wesley Publishing Co. (1999)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ahmadreza Baghaie
    • 1
  • Zeyun Yu
    • 2
  • Roshan M. D’souza
    • 3
  1. 1.Department of Electrical EngineeringUniversity of Wisconsin-MilwaukeeUSA
  2. 2.Department of Computer ScienceUniversity of Wisconsin-MilwaukeeUSA
  3. 3.Department of Mechanical EngineeringUniversity of Wisconsin-MilwaukeeUSA

Personalised recommendations