A Novel Nonrigid Registration Algorithm and Applications (original) (raw)

Abstract

In this paper we describe a new algorithm for nonrigid registration of brain images based on an elastically deformable model. The use of registration methods has become an important tool for computer-assisted diagnosis and surgery. Our goal was to improve analysis in various applications of neurology and neurosurgery by improving nonrigid registration. A local gray level similarity measure is used to make an initial sparse displacement field estimate. The field is initially estimated at locations determined by local features, and then a linear elastic model is used to infer the volumetric deformation across the image. The associated partial differential equation is solved by a finite element approach. A model of empirically observed variability of the brain was created from a dataset of 154 young adults. Both homogeneous and inhomogeneous elasticity models were compared. The algorithm has been applied to medical applications including intraoperative images of neurosurgery showing brain shift and a study of gait and balance disorder.

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Author information

Authors and Affiliations

  1. Surgical Planning Laboratory, Harvard Medical School & Brigham and Women’s Hospital, 75 Francis St., Boston, MA, 02115, USA
    J. Rexilius, S. K. Warfield, C. R. G. Guttmann, X. Wei, M. Shenton & R. Kikinis
  2. Department of Neurology, University of Connecticut Health Center, USA
    R. Benson & L. Wolfson
  3. Institute for Medical Informatics, Medical University of Luebeck, Germany
    H. Handels

Authors

  1. J. Rexilius
  2. S. K. Warfield
  3. C. R. G. Guttmann
  4. X. Wei
  5. R. Benson
  6. L. Wolfson
  7. M. Shenton
  8. H. Handels
  9. R. Kikinis

Editor information

Editors and Affiliations

  1. Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
    Wiro J. Niessen & Max A. Viergever &

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© 2001 Springer-Verlag Berlin Heidelberg

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Rexilius, J. et al. (2001). A Novel Nonrigid Registration Algorithm and Applications. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3\_110

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