Hybrid Multiscale Landmark and Deformable Image Registration

Abstract

An image registration technique is presented for the registration of medical images using a hybrid combination of coarse-scale landmark and B-splines deformable registration techniques. The technique is particularly effective for registration problems in which the images to be registered contain large localized deformations. A brief overview of landmark and deformable registration techniques is presented. The hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese, A multiscale image representation using hierarchical (BV;L2) decompositions, Multiscale Modeling and Simulations, vol. 2, no. 4, pp. 554{579, 2004, is reviewed, and an image registration algorithm is developed based on combining the multiscale decomposition with landmark and deformable techniques. Successful registration of medical images is achieved by first obtaining a hierarchical multiscale decomposition of the images and then using landmark-based registration to register the resulting coarse scales. Corresponding bony structure landmarks are easily identified in the coarse scales, which contain only the large shapes and main features of the image. This registration is then fine tuned by using the resulting transformation as the starting point to deformably register the original images with each other using an iterated multiscale B-splines deformable registration technique. The accuracy and efficiency of the hybrid technique is demonstrated with several image registration case studies in two and three dimensions. Additionally, the hybrid technique is shown to be very robust with respect to the location of landmarks and presence of noise.

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Document Details

Document Type
Technical Report
Publication Date
Apr 11, 2007
Accession Number
ADA518734

Entities

People

  • Dana Paquin
  • Doron Levy
  • Lei Xing

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Computations
  • Data Processing
  • Diagnostic Imaging
  • Equations
  • Gaussian Noise
  • Identification
  • Image Processing
  • Image Registration
  • Impulse Noise
  • Mathematics
  • Noise
  • Pattern Recognition
  • Target Recognition
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Computer Vision.