Skip to main content

A Hyperelastic Deformable Template for Cardiac Segmentation in MRI

  • Conference paper
Functional Imaging and Modeling of the Heart (FIMH 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4466))

  • 1296 Accesses

Abstract

This article proposes a hyperelastic 3D deformable template for the segmentation of soft structures. It relies on a template, which is a topological, geometrical and material model of the structure to segment. The template is modeled as an elastic body which is deformed by forces derived from the image. The proposed model is based on the nonlinear three-dimensional elasticity problem with a boundary condition of pure traction. In addition, the applied forces depend on the displacements. For computations, a convergent algorithm is proposed to minimize the global energy of template deformation. A discrete algorithm using the finite element method is presented and illustrated on MR images of mice.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Veress, AI., Gullberg, GT., Weiss, JA.: Measurement of strain in the left ventricle during diastole with cine-MRI and deformable image registration. J Biomech Eng 7(127), 207–1195 (2005)

    Google Scholar 

  2. Borgefors, G.: Distance transformation in digital images. Computer Vision Graphics and Image Processing 48, 344–371 (1986)

    Article  Google Scholar 

  3. Borouchaki, H., George, P.L.: Triangulation de Delaunay et métrique riemannienne. Applications aux maillages éléments finis. Rev. Européenne Élém. Finis 5(3), 323–340 (1996)

    MATH  MathSciNet  Google Scholar 

  4. Canny, J.F.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 679–698 (1986)

    Article  Google Scholar 

  5. Ciarlet, P.G.: Mathematical elasticity. Vol. I. In: Studies in Mathematics and its Applications, vol. 20, North-Holland Publishing Co., Amsterdam (1988)

    Google Scholar 

  6. Frangi, A.F., Rueckert, D., Schnabel, J.A., Niessen, W.J.: Automatic construction of multiple-object three-dimensional statistical shape models. IEEE Transactions on Medical Imaging 21(9), 1151–1166 (2002)

    Article  Google Scholar 

  7. Kaus, M.R., von Berg, J., Weese, J., Niessen, W., Pekar, V.: Automated segmentation of the left ventricle in cardiac MRI. Medical Image Analysis 8, 245–254 (2004)

    Article  Google Scholar 

  8. Klein, G.J., Huesman, R.H.: Four-dimensional processing of deformable cardiac PET data. Medical Image Analysis 6, 29–46 (2002)

    Article  Google Scholar 

  9. Lötjönen, J., Kivistö, S., Koikkalainen, J., Smutek, D., Lauerma, K.: Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images. Medical Image Analysis 8, 371–386 (2004)

    Article  Google Scholar 

  10. Mäkelä, T., Pham, Q.C., Clarysse, P., Nenonen, J., Lötjönen, J., Sipilä, O., Hänninen, H., Lauerma, K., Knuuti, J., Katila, T., Magnin, I.E.: A 3-D model-based registration approach for the PET, MR and MCG cardiac data fusion. Medical Image Analysis 7, 377–389 (2003)

    Article  Google Scholar 

  11. Mitchell, S.C., Bosch, J.G., Lelieveldt, B.P.F., van der Geest, R.J., Reiber, J.H.C., Sonka, M.: 3D active appearance models: segmentation of cardiac MR and ultrasound images. IEEE Transactions on Medical Imaging 21(9), 1167–1178 (2002)

    Article  Google Scholar 

  12. Montagnat, J., Delingette, H.: A review of deformable surfaces: topology, geometry and deformation. Image and Vision Computing 19(14), 1023–1040 (2001)

    Article  Google Scholar 

  13. Osher, S., Sethian, J.A.: Fronts propagating with curvature-dependent speed: algorithms based on hamilton-jacobi formulations. J. Comput. Phys. 79(1), 12–49 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  14. Pham, Q.-C., Vincent, F., Clarysse, P., Croisille, P., Magnin, I.E.: A FEM-based deformable model for the 3D segmentation and tracking of the heart in cardiac MRI. In: 2nd International Symposium on Image and Signal Processing and Analysis (ISPA 2001), vol. 1, pp. 250–254, Pula, Croatia (2001)

    Google Scholar 

  15. Picq, M., Pousin, J., Rouchdy, Y.: A Linear 3D Elastic Segmentation Model for Vector Fields. Application to the Heart segmentation in MRI. To be published in Journal of Mathematical Imaging and Vision (2007)

    Google Scholar 

  16. Rabbitt, R., Weiss, J., Christensen, G.: Mapping of hyper-elastic deformable templates using the finite element method. In: Kučera, L. (ed.) WG 2002, LNCS vol. 2573, pp. 252–265. Springer, Heidelberg (2002)

    Google Scholar 

  17. Rouchdy, Y., Pousin, J., Schaerer, J., Clarysse, P.: A nonlinear elastic deformable template for soft structure segmentation. Application to the heart segmentation in MRI. Accepted in Inverse Problems (2007)

    Google Scholar 

  18. Saito, T., Toriwaki, T.I.: New algorithm for euclidean distance transformation of an n-dimensional digitized picture with applications. Pattern recognition 27, 1551–1565 (1994)

    Article  Google Scholar 

  19. Schaerer, J., Rouchdy, Y., Clarysse, P., Hiba, B., Croisille, P., Pousin, J., Magnin, I.E.: Simultaneous segmentation of the left and right heart ventricles in 3D cine MR images of small animals. In: Proceedings of Computers in Cardiology, pp. 231–234, Lyon (2005)

    Google Scholar 

  20. Schaerer, J., Qian, Z., Clarysse, P., Metaxas, D., Axel, L., Magnin, I.E.: Fast and automated creation of patient-specific 3d heart models from tagged mri. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, Springer, Heidelberg (2006)

    Google Scholar 

  21. Xu, C., Prince, J.L.: Snakes, shapes and gradient vector flow. IEEE Trans. Image Processing 7, 359–369 (1998)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Frank B. Sachse Gunnar Seemann

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Rouchdy, Y., Pousin, J., Schaerer, J., Clarysse, P. (2007). A Hyperelastic Deformable Template for Cardiac Segmentation in MRI. In: Sachse, F.B., Seemann, G. (eds) Functional Imaging and Modeling of the Heart. FIMH 2007. Lecture Notes in Computer Science, vol 4466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72907-5_45

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72907-5_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72906-8

  • Online ISBN: 978-3-540-72907-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics