Contour-model-guided nonlinear deformation model for inter-subject image registration

Wen Shiang V Shih, Wei Chung Lin, Chin Tu Chen

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


An automated method is proposed for anatomic standardization that can elastically map one subject's MRI image to a standard reference MRI image to enable inter-subject and cross-group studies. In this method, linear transformations based on bicommissural stereotaxy are first applied to grossly align the input image to the reference image. Then, generalized Hough transform is applied to find the candidate corresponding regions in the input image based on the contour information from the pre-segmented reference image. Next, an active contour model initialized with the result from the generalized Hough transform is employed to refine the contour description of the input image. Based on the contour correspondence established in the previous steps, a non-linear transformation is determined using the proposed weighted local reference coordinate systems to warp the input image. In this method, geometric correspondence established based on contour matching is used to control the warping and the actual image values corresponding to registered coordinates need not be similar. We tested this algorithm on various synthetic and real images for inter- subject registration of MR images.

Original languageEnglish (US)
Pages (from-to)611-620
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Dec 1 1997
EventMedical Imaging 1997: Image Processing - Newport Beach, CA, United States
Duration: Feb 25 1997Feb 25 1997


  • Deformable model
  • Image registration

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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