Abstract
We present an algorithm for solid organ registration of pre-segmented data represented as tetrahedral meshes. Registration of the organ surface is driven by force terms based on a distance field representation of the source and reference shapes. Registration of internal morphology is achieved using a non-linear elastic finite element model. A key feature of the method is that the user does not need to specify boundary conditions (surface point correspondences) prior to the finite element analysis. Instead the boundary matches are found as an integrated part of the analysis. The method is evaluated on phantom data and prostate data obtained in vivo based on fiducial marker accuracy and inverse consistency of transformations. The parallel nature of the method allows an efficient implementation on a GPU and as a result the method is very fast. All validation registrations take less than 30 seconds to complete. The proposed method has many potential uses in image guided radiotherapy (IGRT) which relies on registration to account for organ deformation between treatment sessions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Noe, K.Ø., Mosegaard, J., Tanderup, K., Sørensen, T.S.: A framework for shape matching in deformable image registration. Stud. Health. Technol. Inform. 132, 333–335 (2008)
Marchal, M., Promayon, E., Troccaz, J.: Simulating prostate surgical procedures with a discrete soft tissue model. In: Workshop in Virtual Reality and Physical Simulation (2006)
Hagemann, A., Rohr, K., Stiehl, H.S., Spetzger, U., Gilsbach, J.M.: Biomechanical modeling of the human head for physically based, nonrigid image registration. IEEE transactions on medical imaging 18, 875–882 (1999)
Hagemann, A., Rohr, K., Stiehl, H.S.: Coupling of fluid and elastic models for biomechanical simulations of brain deformations using fem. Medical Image Analysis 6(4), 375–388 (2002)
Schnabel, J., Tanner, C., Castellano-Smith, A., Degenhard, A., Leach, M., Hose, D., Hill, D., Hawkes, D.: Validation of nonrigid image registration using finite-element methods: application to breast mr images. IEEE Transactions on Medical Imaging 22(2), 238–247 (2003)
Yan, D., Jaffray, D.A., Wong, J.W.: A model to accumulate fractionated dose in a deforming organ. International Journal of Radiation Oncology*Biology*Physics 44(3), 665–675 (1999)
Ferrant, M., Warfield, S.K., Nabavi, A., Jolesz, F.A., Kikinis, R.: Registration of 3d intraoperative mr images of the brain using a finite element biomechanical model. IEEE Transactions on Medical Imaging, 1384–1397 (2001)
Bharatha, A., Hirose, M., Hata, N., Warfield, S.K., Ferrant, M., Zou, K.H., Suarez-Santana, E., Ruiz-Alzola, J., D’Amico, A., Cormack, R.A., Kikinis, R., Jolesz, F.A., Tempany, C.M.C.: Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging. Medical Physics 28, 2551–2560 (2001)
Brock, K.K., Sharpe, M.B., Dawson, L.A., Kim, S.M., Jaffray, D.A.: Accuracy of finite element model-based multi-organ deformable image registration. Medical Physics 32(6), 1647–1659 (2005)
Brock, K.K., Dawson, L.A., Sharpe, M.B., Moseley, D.J., Jaffray, D.A.: Feasibility of a novel deformable image registration technique to facilitate classification, targeting, and monitoring of tumor and normal tissue. Int. J. Radiat. Oncol. Biol. Phys. 64(4), 1245–1254 (2006)
Brock, K.K., McShan, D.L., Haken, R.K.T., Hollister, S.J., Dawson, L.A., Balter, J.M.: Inclusion of organ deformation in dose calculations. Medical Physics 30(3), 290–295 (2003)
Liang, J., Yan, D.: Reducing uncertainties in volumetric image based deformable organ registration. Med. Phys. 30, 2116–2122 (2003)
Picinbono, G., Delingette, H., Ayache, N.: Nonlinear and anisotropic elastic soft tissue models for medical simulation. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), 2001, vol. 2, pp. 1370–1375 (2001)
Choi, J., Szymczak, A.: Fitting solid meshes to animated surfaces using linear elasticity. ACM Trans. Graph. 28(1), 1–10 (2009)
Zhang, T., Orton, N.P., Mackie, T.R., Paliwal, B.R.: Technical note: A novel boundary condition using contact elements for finite element based deformable image registration. Medical Physics 31(9), 2412–2415 (2004)
Haker, S., Warfield, S.K., Tempany, C.M.: Landmark-guided surface matching and volumetric warping for improved prostate biopsy targeting and guidance. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 853–861. Springer, Heidelberg (2004)
Angenent, S., Haker, S., Tannenbaum, A., Kikinis, R.: On the laplace-beltrami operator and brain surface flattening. IEEE Transactions on Medical Imaging 18(8), 700–711 (1999)
Haker, S., Angenent, S., Tannenbaum, A., Kikinis, R., Sapiro, G., Halle, M.: Conformal surface parameterization for texture mapping. IEEE Transactions on Visualization and Computer Graphics 6(2), 181–189 (2000)
Warfield, S.K., Haker, S.J., Talos, I.F., Kemper, C.A., Weisenfeld, N., Mewes, A.U., Goldberg-Zimring, D., Zou, K.H., Westin, C.F., Wells, W.M., Tempany, C.M., Golby, A., Black, P.M., Jolesz, F.A., Kikinis, R.: Capturing intraoperative deformations: research experience at brigham and women’s hospital. Medical Image Analysis 9(2), 145–162 (2005)
Marai, G.E., Laidlaw, D.H., Crisco, J.J.: Super-resolution registration using tissue-classified distance fields. IEEE transactions on medical imaging 25, 177–187 (2006)
Paragios, N., Rousson, M., Ramesha, V.: Non-rigid registration using distance functions. In: Computer Vision and Image Understanding, pp. 142–165 (2003)
Xiao, G., Ong, S., Foong, K.: 3d registration of partially overlapping surfaces using a volumetric approach. Image and Vision Computing 25(6), 934–944 (2007)
Labelle, F., Shewchuk, J.R.: Isosurface stuffing: fast tetrahedral meshes with good dihedral angles. In: SIGGRAPH 2007: ACM SIGGRAPH 2007 papers, p. 57. ACM, New York (2007)
Miller, C., Joldes, G., Lance, D., Wittek, A.: Total lagrangian explicit dynamics finite element algorithm for computing soft tissue deformation. Communications in Numerical Methods in Engineering 23(2), 121–134 (2006)
Taylor, Z.A., Cheng, M., Ourselin, S.: High-speed nonlinear finite element analysis for surgical simulation using graphics processing units. IEEE Transactions on Medical Imaging 27(5), 650–663 (2008)
Xu, C., Prince, J.: Snakes, shapes, and gradient vector flow. IEEE Transactions on Image Processing 7(3), 359–369 (1998)
Söhn, M., Birkner, M., Yan, D., Alber, M.: Modelling individual geometric variation based on dominant eigenmodes of organ deformation: implementation and evaluation. Physics in Medicine and Biology 50, 5893–5908 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Noe, K.Ø., Sørensen, T.S. (2010). Solid Mesh Registration for Radiotherapy Treatment Planning. In: Bello, F., Cotin, S. (eds) Biomedical Simulation. ISBMS 2010. Lecture Notes in Computer Science, vol 5958. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11615-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-11615-5_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11614-8
Online ISBN: 978-3-642-11615-5
eBook Packages: Computer ScienceComputer Science (R0)