Subscribe to RSS
DOI: 10.1160/ME9045
Spatially Varying Elasticity in Image Registration
Publication History
Publication Date:
20 January 2018 (online)
Summary
Objectives: In this paper we are concerned with elastic image registration. Usually, elastic approaches assume constant material parameters and result in a smooth displacement field. However, a constant choice has its shortcomings for images with varying elastic properties, like bones and soft tissue. The proposed method allows forspatially varying material properties.
Methods: The proposed variational registration scheme is based on a segmentation of the template image. Individual material properties can be assigned to each segmented region. The proposed variable elastic regulariser leads to a displacement field which is adapted to the locally chosen material properties.
Results: The capability of this approach is demonstrated by a synthetic and by real-life examples in two dimensions. For all examples the proposed method is compared to a conventional scheme where the material parameters are constants in the entire image domain.
Conclusions: A method for non-parametric registration which supports spatially varying elastic properties such as (in)compressibility or Young’s modulus in certain image regions is proposed. It allows for registration results to be more realistic compared to conventional approaches. Also, for a particular structure, an approximated preservation of volume or shape can be achieved.
-
References
- 1 Modersitzki J. Numerical methods for image registration. Oxford: Oxford University Press; 2004
- 2 Edwards PJ, Hill DLG, Little JA, Hawkes DJ. A three-component deformation model for image guided surgery. Medical Image Analysis. 1998; 02 (04) 355-367.
- 3 Duay V, D’Haese P-F, Li R, Dawant BM. Nonrigid registration algorithm with spatially varying stiffness properties. IEEE International Symposium on Biomedical Imaging: ISBI. 2004. Arlington, USA: IEEE; 2004: 408-411.
- 4 Staring M, Klein S, Pluim J. Nonrigid registration with adaptive, content-based filtering of the deformation field. Fitzpatrick JM, Reinhardt JM. Medical Imaging 2005: Image Processing. Proceedings of the SPIE; 2005. San Diego, USA: SPIE; 2005: 212-221.
- 5 Davatzikos C. Nonlinear registration of brain images using deformable models. Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA ‘96); 1996. San Francisco, USA: IEEE; 1996: 94-103.
- 6 Ferrant M, Nabavi A, Jolesz FA, Kikinis R, War-field SK. Registration of 3-d intraoperative MR images of the brain using a finite-element bio-mechanical model. IEEE Transactions on Medical Imaging 2001; 20 (12) 1384-1397.
- 7 Ecabert O, Butz T, Nabavi A, Thiran JP. Brain shift correction based on a boundary element bio-mechanical model with different material properties. Ellis RE, Peters TM. Medical Image Computing and Computer-Assisted Intervention – MICCAI2003, Proceedings of the 6th International Conference; 2003. Montreal, Canada. Berlin: Springer; 2003: 41-49.
- 8 Hagemann A, Rohr K, Stiehl HS, Spetzger U, Gilsbach JM. Biomechanical modeling of the human head for physically-based, non-rigid image registration. IEEE Transactions on Medical Imaging 1999; 18 (10) 875-884.
- 9 Rexilius J, Handels H, Nabavi A, Kikinis R, War-field SK. Automatic nonrigid registration for tracking brain shift during neurosurgery. Meiler M, Saupe D, Kruggel F, Handels H, Lehmann T. Bildverarbeitung für die Medizin 2002, Algorithmen – Systeme – Anwendungen. BVM 2002: Proceedings des Workshops; 2002. Leipzig, Germany. Berlin: Springer; 2002: 135-138.
- 10 Ehrhardt J, Handels H, Strathmann B, Malina T, Plötz W, Pöppl SJ. Atlas-based recognition of anatomical structures and landmarks to support the virtual three-dimensional planning of hip operations. Ellis RE, Peters TM. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2003, Proceedings of the 6th International Conference; 2003. Montreal, Canada. Berlin: Springer; 2003: 17-24.
- 11 Kabus S, Franz A, Fischer B. On elastic image registration with varying material parameters. Meinzer H-P, Handels H, Horsch A, Tolxdorff T. Bildverarbeitung für die Medizin 2005, Algorithmen – Systeme – Anwendungen. BVM 2005: Proceedings des Workshops; 2005. Heidelberg, Germany. Berlin: Springer; 2005: 330-334.
- 12 Kabus S, Franz A, Fischer B. Variational image registration with local properties. Pluim JPW, Likar B, Gerritsen FA. Biomedical Image Registration. WBIR 2006: Proceedings of the Third International Workshop; 2006. Utrecht, The Netherlands. Berlin: Springer; 2006: 92-100.
- 13 Bystrov D, Pekar V, Meetz K, Schulz H, Netsch T. Motion compensation and plane tracking for kinematic MR-imaging. Liu Y, Jiang T, Zhang C. Computer Vision for Biomedical Image Applications. CVBIA 2005: Proceedings of the First International Workshop; 2005. Beijing, China. Berlin: Springer; 2005: 551-560.
- 14 Bookstein FL. Principal Warps: Thin-Plate Splines and the Decomposition of Deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence 1989; 11 (06) 567-585.