Fast Explicit Diffusion for Registration with Direction-Dependent Regularization
The accurate estimation of respiratory lung motion by non-linear registration is currently an important topic of research and required for many applications in pulmonary image analysis, e.g. for radiotherapy treatment planning.
A special challenge for lung registration is the sliding motion between visceral an parietal pleurae during breathing, which causes discontinuities in the motion field. It has been shown that accounting for this physiological aspect by modeling the sliding motion using a direction-dependent regularization approach can significantly improve registration results. While the potential of such physiology-based regularization methods has been demonstrated in several publications, so far only simple explicit solution schemes were applied due to the computational complexity.
In this paper, a numerical solution of the direction-dependent regularization based on Fast Explicit Diffusion (FED) is presented. The approach is tested for motion estimation on 23 thoracic CT images and a significant improvement over the classic explicit solution is shown.
KeywordsMotion Estimation Object Boundary Explicit Scheme Template Image Target Registration Error
Unable to display preview. Download preview PDF.
- 2.Delmon, V., Rit, S., Pinho, R., Sarrut, D.: Direction dependent B-splines decomposition for the registration of sliding objects. In: Fourth International Workshop on Pulmonary Image Analysis, MICCAI 2011, pp. 45–55 (2011)Google Scholar
- 7.Nagel, H.H., Enkelmann, W.: An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences. IEEE Trans. Pattern Anal. Mach. Intell. (5), 565–593 (1986)Google Scholar
- 8.Pace, D.F., Enquobahrie, A., Yang, H., Aylward, S.R., Niethammer, M.: Deformable Image Registration of Sliding Organs Using Anisotropic Diffusive Regularization. In: Proc IEEE Int. Symp. Biomed. Imaging, pp. 407–413 (2011)Google Scholar
- 9.Risser, L., Baluwala, H., Schnabel, J.A.: Diffeomorphic registration with sliding conditions: Application to the registration of lungs CT images. In: Fourth International Workshop on Pulmonary Image Analysis, MICCAI 2011, pp. 79–90 (2011)Google Scholar
- 10.Ruan, D., Esedoglu, S., Fessler, J.: Discriminative sliding preserving regularization in medical image registration. In: Proc. IEEE Int. Symp. Biomed. Imaging, pp. 430–433 (2009)Google Scholar
- 12.Vandemeulebroucke, J., Sarrut, D., Clarysse, P.: The POPI-model, a point-validated pixel-based breathing thorax model. In: International Conference on the Use of Computers in Radiation Therapy, ICCR (2007)Google Scholar
- 14.Werner, R., Ehrhardt, J., Schmidt-Richberg, A., Handels, H.: Validation and comparison of a biophysical modeling approach and non-linear registration for estimation of lung motion fields in thoracic 4D CT data. In: Proc. SPIE, p. 72590U (2009)Google Scholar