Abstract
Discontinuous motion is quite common in the medical field as for example in the case of breathing induced organ motion. Registration methods that are able to preserve discontinuities are therefore of special interest. To achieve this goal we developed in our previous work a framework that combines motion segmentation and registration. To avoid unreliable motion fields the incorporation of landmark correspondences can be a remedy. We therefore describe in this paper how we integrate the landmarks in our variational approach and how to solve the minimisation problem with a primal-dual algorithm. Qualitative and quantitative results are shown for real MR images of breathing induced liver motion.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Amiaz, T., Kiryati, N.: Piecewise-Smooth Dense Optical Flow via Level Sets. International Journal of Computer Vision 68(2), 111–124 (2006)
Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High Accuracy Optical Flow Estimation Based on a Theory for Warping. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 25–36. Springer, Heidelberg (2004)
Brox, T., Malik, J.: Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(3), 500–513 (2011)
Chambolle, A., Pock, T.: A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging. Journal of Mathematical Imaging and Vision 40(1), 120–145 (2011)
Chan, T.F., Esedoglu, S., Nikolova, M.: Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models. Siam Journal on Applied Mathematics 66(5), 1632–1648 (2006)
Demirovic, D., Serifovic, A., Cattin, P.C.: An anisotropic diffusion regularized demons for improved registration of sliding organs. In: 18th International Electrotechnical and Computer Science Conference, ERK (2009)
Haber, E., Heldmann, S., Modersitzki, J.: A Scale-Space Approach to Landmark Constrained Image Registration. Scale Space and Variational Methods in Computer Vision 5567, 612–623 (2009)
Johnson, H., Christensen, G.: Consistent Landmark and Intensity-Based Image Registration. IEEE Transactions on Medical Imaging 21(5), 450–461 (2002)
Kiriyanthan, S., Fundana, K., Cattin, P.C.: Discontinuity Preserving Registration of Abdominal MR Images with Apparent Sliding Organ Motion. In: Yoshida, H., Sakas, G., Linguraru, M.G. (eds.) Abdominal Imaging 2011. LNCS, vol. 7029, pp. 231–239. Springer, Heidelberg (2012)
Kiriyanthan, S., Fundana, K., Majeed, T., Cattin, P.C.: Discontinuity Preserving Registration through Motion Segmentation: A Primal-Dual Approach (submitted)
Kiriyanthan, S., Fundana, K., Majeed, T., Cattin, P.C.: A Primal-Dual Approach for Discontinuity Preserving Registration. In: 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 350–353 (May 2012)
Kybic, J., Unser, M.: Fast Parametric Elastic Image Registration. IEEE Transactions on Image Processing 12(11), 1427–1442 (2003)
Mumford, D., Shah, J.: Optimal Approximations by Piecewise Smooth Functions and Associated Variational-Problems. Communications on Pure and Applied Mathematics 42(5), 577–685 (1989)
Paquin, D., Levy, D., Xing, L.: Hybrid Multiscale Landmark and Deformable Image Registration. Mathematical Biosciences and Engineering 4(4), 711–737 (2007)
Pock, T., Urschler, M., Zach, C., Beichel, R.R., Bischof, H.: A Duality Based Algorithm for TV-L 1-Optical-Flow Image Registration. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 511–518. Springer, Heidelberg (2007)
Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear Total Variation Based Noise Removal Algorithms. Physica D 60(1-4), 259–268 (1992)
Schmidt-Richberg, A., Ehrhardt, J., Werner, R., Handels, H.: Slipping Objects in Image Registration: Improved Motion Field Estimation with Direction-Dependent Regularization. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part I. LNCS, vol. 5761, pp. 755–762. Springer, Heidelberg (2009)
Vese, L.A., Chan, T.F.: A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model. J. of Computer Vision 50(3), 271–293 (2002)
Yu, G., Morel, J.M.: ASIFT: An Algorithm for Fully Affine Invariant Comparison. Image Processing On Line (2011), doi: http://dx.doi.org/10.5201/ipol.2011.my-asift
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kiriyanthan, S., Fundana, K., Majeed, T., Cattin, P.C. (2012). A Landmark-Based Primal-Dual Approach for Discontinuity Preserving Registration. In: Yoshida, H., Hawkes, D., Vannier, M.W. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2012. Lecture Notes in Computer Science, vol 7601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33612-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-33612-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33611-9
Online ISBN: 978-3-642-33612-6
eBook Packages: Computer ScienceComputer Science (R0)