Registration of Cortical Anatomical Structures via Robust 3D Point Matching

  • Haili Chui
  • James Rambo
  • James Duncan
  • Robert Schultz
  • Anand Rangarajan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1613)


Inter-subject non-rigid registration of cortical anatomical structures as seen in MR is a challenging problem. The variability of the sulcal and gyral patterns across patients makes the task of registration especially difficult regardless of whether voxel- or feature-based techniques are used. In this paper, we present an approach to matching sulcal point features interactively extracted by neuroanatomical experts. The robust point matching (RPM) algorithm is used to find the optimal affine transformations for matching sulcal points. A 3D linearly interpolated non-rigid warping is then generated for the original image volume. We present quantitative and visual comparisons between Talairach, mutual information-based volumetric matching and RPM on five subjects’ MR images.


Iterate Close Point Landmark Point Probabilistic Atlas Correspondence Matrix Gyral Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Haili Chui
    • 1
  • James Rambo
    • 1
  • James Duncan
    • 1
  • Robert Schultz
    • 1
  • Anand Rangarajan
    • 1
  1. 1.Departments of Diagnostic Radiology, Electrical Engineering and Yale Child Study CenterYale UniversityNew HavenUSA

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