A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations

  • Julia A. Schnabel
  • Daniel Rueckert
  • Marcel Quist
  • Jane M. Blackall
  • Andy D. Castellano-Smith
  • Thomas Hartkens
  • Graeme P. Penney
  • Walter A. Hall
  • Haiying Liu
  • Charles L. Truwit
  • Frans A. Gerritsen
  • Derek L. G. Hill
  • David J. Hawkes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2208)

Abstract

This work presents a framework for non-rigid registration which extends and generalizes a previously developed technique by Rueckert et al. [1]. We combine multi-resolution optimization with free-form deformations (FFDs) based on multi-level B-splines to simulate a non-uniform control point distribution. We have applied this to a number of different medical registration tasks to demonstrate its wide applicability, including interventional MRI brain tissue deformation compensation, breathing motion compensation in liver MRI, intramodality inter-modality registration of pre-operative brain MRI to CT electrode implant data, and inter-subject registration of brain MRI. Our results demonstrate that the new algorithm can successfully register images with an improved performance, while achieving a significant reduction in run-time.

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References

  1. 1.
    D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes. Non-rigid registration using Free-Form Deformations: Application to breast MR images. IEEE Transactions on Medical Imaging, 18(8):712–721, 1999.CrossRefGoogle Scholar
  2. 2.
    H. Lester and S. R. Arridge. A survey of hierarchical non-linear medical image registration. Pattern Recognition, 32(1):129–149, 1999.CrossRefGoogle Scholar
  3. 3.
    J. V. Hajnal, D. L. G. Hill, and D. J. Hawkes. Medical image registration. CRC Press, 2001.Google Scholar
  4. 4.
    S. Lee, G. Wolberg, and S. Y. Shin. Scattered data interpolation with multilevel B-splines. IEEE Transactions on Visualization and Computer Graphics, 3(3):228–244, 1997.CrossRefGoogle Scholar
  5. 5.
    C. Studholme, D. L. G. Hill, and D. J. Hawkes. An overlap entropy measure of 3D medical image alignment. Pattern Recognition, 32:71–86, 1999.CrossRefGoogle Scholar
  6. 6.
    D. R. Forsey and R. H. Bartels. Hierarchical B-spline refinement. ACM Transactions on Computer Graphics, 22(4):205–212, 1988.CrossRefGoogle Scholar
  7. 7.
    L. Piegl and W. Tiller. The NURBS Book. Springer Verlag, 1997.Google Scholar
  8. 8.
    G. K. Rohde, A. Aldroubi, and B. M. Dawant. Adaptive free-form deformations for interpatient medical image registration. In Proc. Medical Imaging: Image Processing. SPIE, 2001. In press.Google Scholar
  9. 9.
    C. R. Maurer Jr., D. L. G. Hill, A. J. Martin, H. Liu, M. McCue, D. Rueckert, D. Lloret, W. A. Hall, R. E. Maxwell, D. J. Hawkes, and C. L. Truwit. Investigation of intraoperative brain deformation using a 1.5T interventional MR system: preliminary results. IEEE Transactions on Medical Imaging, 17(5):817–825, 1998.CrossRefGoogle Scholar
  10. 10.
    J. A. Schnabel, C. Tanner, A. Castellano Smith, M. O. Leach, C. Hayes, A. Degenhard, R. Hose, D. L. G. Hill, and D. J. Hawkes. Validation of non-rigid registration using Finite Element Methods. In Proc. Information Processing in Medical Imaging (IPMI’01), volume 2082 of Lecture Notes in Computer Science, pages 344–357. Springer Verlag, 2001.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Julia A. Schnabel
    • 1
  • Daniel Rueckert
    • 2
  • Marcel Quist
    • 3
  • Jane M. Blackall
    • 1
  • Andy D. Castellano-Smith
    • 1
  • Thomas Hartkens
    • 1
  • Graeme P. Penney
    • 1
  • Walter A. Hall
    • 4
  • Haiying Liu
    • 5
  • Charles L. Truwit
    • 5
  • Frans A. Gerritsen
    • 3
  • Derek L. G. Hill
    • 1
  • David J. Hawkes
    • 1
  1. 1.Computational Imaging Science Group, Radiological Sciences and Medical EngineeringGuy’s Hospital, King’s CollegeLondonUK
  2. 2.Visual Information Processing, Dept. ComputingImperial College of Science, Technology and MedicineLondonUK
  3. 3.EasyVision Advanced DevelopmentPhilips Medical SystemsBest
  4. 4.Dept. NeurosurgeryUniversity of MinnesotaMinneapolisUSA
  5. 5.Dept. RadiologyUniversity of MinnesotaMinneapolisUSA

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