Integrated Intensity and Point-Feature Nonrigid Registration

  • Xenophon Papademetris
  • Andrea P. Jackowski
  • Robert T. Schultz
  • Lawrence H. Staib
  • James S. Duncan
Conference paper

DOI: 10.1007/978-3-540-30135-6_93

Volume 3216 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Papademetris X., Jackowski A.P., Schultz R.T., Staib L.H., Duncan J.S. (2004) Integrated Intensity and Point-Feature Nonrigid Registration. In: Barillot C., Haynor D.R., Hellier P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg

Abstract

In this work, we present a method for the integration of fea- ture and intensity information for non rigid registration. Our method is based on a free-form deformation model, and uses a normalized mu- tual information intensity similarity metric to match intensities and the robust point matching framework to estimate feature (point) correspon- dences. The intensity and feature components of the registration are posed in a single energy functional with associated weights. We com- pare our method to both point-based and intensity-based registrations. In particular, we evaluate registration accuracy as measured by point landmark distances and image intensity similarity on a set of seventeen normal subjects. These results suggest that the integration of intensity and point-based registration is highly effective in yielding more accurate registrations.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Xenophon Papademetris
    • 1
    • 2
  • Andrea P. Jackowski
    • 3
  • Robert T. Schultz
    • 2
    • 3
  • Lawrence H. Staib
    • 1
    • 2
  • James S. Duncan
    • 1
    • 2
  1. 1.Department of Biomedical EngineeringYale University New HavenUSA
  2. 2.Department of Diag. RadiologyYale University New HavenUSA
  3. 3.Child Study CenterYale University New HavenUSA