Skip to main content
Log in

Matching 3-D anatomical surfaces with non-rigid deformations using octree-splines

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

This paper presents a new method for determining the minimal non-rigid deformation between two 3-D surfaces, such as those which describe anatomical structures in 3-D medical images. Although we match surfaces, we represent the deformation as a volumetric transformation. Our method performs a least squares minimization of the distance between the two surfaces of interest. To quickly and accurately compute distances between points on the two surfaces, we use a precomputed distance map represented using an octree spline whose resolution increases near the surface. To quickly and robustly compute the deformation, we use a second octree spline to model the deformation function. The coarsest level of the deformation encodes the global (e.g., affine) transformation between the two surfaces, while finer levels encode smooth local displacements which bring the two surfaces into closer registration. We present experimental results on both synthetic and real 3-D surfaces.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • AxelssonO. and BarkerV.A. 1984. Finite Element Solution of Boundary Value Problems: Theory and Computation. Academic Press: Orlando, Florida.

    Google Scholar 

  • BajesyR. and KovacicS. 1989. Multiresolution elastic matching. Computer Vision, Graphics, and Image Processing, 46:1–21.

    Google Scholar 

  • BardinetE., CohenL.D., and AycheN. 1994. Fitting of isosurfaces using superquadrics and free-form deformations. In IEEE Workshop on Biomedical Image Analysis, pp. 184–193, Seattle. IEEE Computer Society.

    Google Scholar 

  • BarrA.H. 1984. Global and local deformations of solid primitives. Computer Graphics (SIGGRAPH'84), 18(3):21–30.

    Google Scholar 

  • BeierT. and NeelyS. 1992. Feature-based image metamorphosis. Computer Graphics (SIGGRAPH'92), 26(2):35–42.

    Google Scholar 

  • BestP.J. and McKayN.D. 1992. A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2):239–256.

    Google Scholar 

  • BittarE., LavalléeS., and SzeliskiR. 1993. A method for registering overlapping range images of arbitrarily shaped surfaces for 3-d object reconstruction. In SPIE Vol. 2059, Sensor Fusion VI, Boston. Society of Photo-Optical Instrumentation Engineers.

    Google Scholar 

  • BooksteinF.L. 1989. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(6):567–585.

    Google Scholar 

  • BorgeforsG. 1986. Distance transformations in digital images. Computer Vision, Graphics, and Image Processing, 34:344–371.

    Google Scholar 

  • BrunieL., LavalléeS., and SzeliskiR. 1992. Using forces fields derived from 3D distance maps for inferring the attitude of a 3D rigid object. In Second European Conference on Computer Vision (ECCV'92), pp. 670–675, Springer Verlag: Santa Margherita, Italy.

    Google Scholar 

  • BurrD.J. 1981. A dynamic model for image registration. Computer Graphics and Image Processing, 15(2):102–112.

    Google Scholar 

  • CarlbomI., TerzopoulosD., and HarrisK.M. 1991. Reconstructing and visualizing models of neuronal dendrites. In N.M.Patrikalakis (Ed.), Scientific Visualization of Physical Phenomena, pp. 623–638. Springer-Verlag: New York.

    Google Scholar 

  • ChamplebouxG., LavalléeS., SzeliskiR., and BrunieL. 1992. From accurate range imaging sensor calibration to accurate model-based 3-D object localization. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'92), pp. 83–89, IEEE Computer Society, Champaign, Illinois.

    Google Scholar 

  • ChristensenG.E., RabbittR.D., and MillerM.I. 1994. 3D brain mapping using a deformable neuronanatomy. Physics in Medicine and Biology, 39:609–618.

    Google Scholar 

  • CohenL.D. and CohenI. 1993. Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11):1131–1147.

    Google Scholar 

  • DanielsonP.-E. 1980. Euclidean distance mapping. Computer Graphics and Image Processing, 14:227–248.

    Google Scholar 

  • Evans, A.C., Dai, W., Collins, L., Neelin, P., and Marett, S. 1991. Warping of a computerized 3-d atlas to match brain image volumes for quantitative neuroanatomical and functional analysis. In SPIE Vol. 1445, Medical Imaging V, pp. 236–247.

  • FeldmarJ. and AyacheN. 1994. Locally affine registration of free-form surfaces. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'94), pp. 496–501, IEEE Computer Society, Seattle, Washington.

    Google Scholar 

  • FeldmarJ. and AyacheN. 1994. Rigid and affine registration of smooth surfaces using differential properties. In Third European Conference on Computer Vision (ECCV'94), Vol. 2, pp. 397–406, Springer-Verlag: Stockholm, Sweden.

    Google Scholar 

  • ForseyD.R. and BartelsR.H. 1988. Hierarchical B-spline refinement. Computer Graphics (SIGGRAPH'88), 22(4):205–212.

    Google Scholar 

  • Garcia, G. 1989. Contribution a la modelisation d'objects et a la detection de collisions en robotique a l'aide d'arbres octaux. Ph.D. thesis, Nantes University.

  • GuéziecA. and AyacheN. 1992. Smoothing and matching of 3-d space curves. In Second European Conference on Computer Vision (ECCV'92), pp. 620–629, Springer Verlag: Santa Margherita, Italy.

    Google Scholar 

  • Hamadeh, A. et al. 1995. Anatomy-based registration for computer-integrated surgery. In First International Conference on Computer Vision, Virtual Reality and Robotics in Medicine (CVRMed'95), Nice, France.

  • HerzenB.V. and BarrA.H. 1995. Accurate triangulations of deformed, intersecting surfaces. Computer Graphics, 21(4):103–110, 1987.

    Google Scholar 

  • HorowitzB. and PentlandA. 1991. Recovery of non-rigid motion and structure. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'91), pp. 325–330, IEEE Computer Society Press: Maui, Hawaii.

    Google Scholar 

  • HuberP.J. 1981. Robust Statistics. John Wiley & Sons: New York.

    Google Scholar 

  • Huttenlocher, D.P., Kedem, K., and Sharir, M. 1991. The upper envelope of Vornoi surfaces and its applications. In Seventh ACM Symposium on Computational Geometry, pp 194–293. To appear in Discrete Computational Geometry.

  • Jacq, J.J. and Roux, C. 1993. Automatic registration of 3D images using a simple genetic algorithm with a stochastic performance function. In IEEE Engineering Medicine Biology Society (EMBS), pp. 126–127, San Diego.

  • Lavallée, S. 1989. Geste Medico-Chirurgicaux Assistes par Ordinateur: Application a la Neurochirurgie Stereotaxique. Ph.D. thesis, Grenoble University, France.

  • Lavallée, S., Brunie, L., Mazier, B., and Cinquin, P. 1991. Matching of medical images for computer and robot assisted surgery. In IEEE EMBS Conference, pp. 39–40, Orlando, Florida.

  • LavalléeS. and SzeliskiR. 1994. Recovering the position and orientation of free-form objects from image contours using 3-D distance maps. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(4):378–390.

    Google Scholar 

  • Lavallée, S., Szeliski, R., and Brunie, L. 1991. Matching 3-D smooth surfaces with their 2-D projections using 3-D distance maps. In SPIE Vol. 1570 Geometric Methods in Computer Vision, pp. 322–336, San Diego, CA.

  • LeitnerS., MarqueI., LavalléeS., and CinquinP. 1991. Dynamic segmentation: Finding the edge with spline snakes. In P.J.Laurent (Ed.), International Conference on Curves and Surfaces, Academic Press: Chamonix.

    Google Scholar 

  • McInerneyT. and TerzopoulosD. 1993. A finite element model for 3D shape reconstruction and nonrigid motion tracking. In Fourth International Conference on Computer Vision (ICCV'93), pp. 518–523, IEEE Computer Society Press: Berlin, Germany.

    Google Scholar 

  • Monga, Ol, Ayache, N., and Sander. P.T. 1991. From voxel to curvature. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'91), pp. 644–649, Maui, Hawaii.

  • Monga, O., Benayoun, S., and Ayache, N. 1992. From partials derivatives of 3D density images to ridge lines. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'92), pp. 354–359, Champaign, Illinois.

  • MongaO., DericheR., MalandrainG., and CocquerezJ.P. 1990. Recursive filtering and edge closing: Two primary tools for 3D edge detection. In First European Conference on Computer Vision (ECCV'90), pp. 56–65, Springer-Verlag: Antibes, France.

    Google Scholar 

  • PaglieroniD.W. 1992. Distance transforms: Properties and machine vision applications. CVGIP: Graphical Models and Image Processing, 54(1):56–74.

    Google Scholar 

  • PelizzariC.A., ChenG.T.Y., SpelbringD.R., WeichselbaumR.R., and ChenC.-T. 1989. Accurate 3-D registration of CT, PET, and-or MR images of the brain. J. Computer Assisted Tomography, 13(1):20–26.

    Google Scholar 

  • PressW.H., FlanneryB.P., TeukolskyS.A., and VetterlingW.T. 1992. Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press: Cambridge, England, second edition.

    Google Scholar 

  • QuamL.H. 1984. Hierarchical warp stereo. In Image Understanding Workshop, pp. 149–155, New Orleans, Louisiana. Science Applications International Corporation.

    Google Scholar 

  • SametH. 1989. The Design and Analysis of Spatial Data Structures. Addison-Wesley: Reading, Massachusetts.

    Google Scholar 

  • SederbergT.W. and ParryS.R. 1986. Free-form deformations of solid geometric models. Computer Graphics (SIGGRAPH'86), 20(4):151–160.

    Google Scholar 

  • SzeliskiR. 1989. Bayesian Modeling of Uncertainty in Low-Level Vision. Kluwer Academic Publishers: Boston, Massachusetts.

    Google Scholar 

  • SzeliskiR. 1990. Fast surface interpolation using hierarchical basis functions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(6):513–528.

    Google Scholar 

  • SzeliskiR. and LavalléeS. 1993. Matching 3-D anatomical surfaces with non-rigid deformations. In SPIE Vol. 2031 Geometric Methods in Computer Vision II, pp. 306–315, San Diego. Society of Photo-Optical Instrumentation Engineers.

    Google Scholar 

  • SzeliskiR. and LavalléeS. 1994. Matching 3-D anatomical surfaces with non-rigid deformations using octree-splines. In IEEE Workshop on Biomedical Image Analysis, pp. 144–153, Seattle, IEEE Computer Society.

    Google Scholar 

  • SzeliskiR. and TerzopoulosD. 1989. Parallel multigrid algorithms and computer vision applications. In Fourth Copper Mountain Conference on Multigrid Methods, pp. 383–398, Copper Mountain, Colorado. Society for Industrial and Applied Mathematics.

    Google Scholar 

  • TerzopoulosD. 1986. Image analysis using multigrid relaxation methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(2):129–139.

    Google Scholar 

  • TerzopoulosD. 1986. Regularization of inverse visual problems involving discontinuities. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(4):413–424.

    Google Scholar 

  • TerzopoulosD. and MetaxasD. 1991. Dynamic 3D models with local and global deformations: Deformable superquadrics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(7):703–714.

    Google Scholar 

  • TerzopoulosD., PlattJ., BarrA., and FleischerK. 1987. Elastically deformable models. Computer Graphics (SIGGRAPH'87), 21(4):205–214.

    Google Scholar 

  • TerzopoulosD., WitkinA., and KassM. 1988. Constraints on deformable models: Recovering 3D shape and nonrigid motion. Artificial Intelligence, 36:91–123.

    Google Scholar 

  • ThirionJ.-P. 1994. Extremal points: Definition and application to 3D image registration. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'94), pp. 587–592, Seattle, IEEE Computer Society.

    Google Scholar 

  • WelchW. and WitkinA. 1992. Variational surface modeling. Computer Graphics (SIGGRAPH'92), 26(2):157–166.

    Google Scholar 

  • WitkinA. and WelchW. 1990. Fast animation and control of non-rigid structures. Computer Graphics (SIGGRAPH'90), 24(4):243–252.

    Google Scholar 

  • YserantantH. 1986. On the multi-level splitting of finite elements spaces. Numerische Mathematik, 49:379–412.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Szeliski, R., Lavallée, S. Matching 3-D anatomical surfaces with non-rigid deformations using octree-splines. Int J Comput Vision 18, 171–186 (1996). https://doi.org/10.1007/BF00055001

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00055001

Keywords

Navigation