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3D Multi-Modality Medical Image Registration Using Feature Space Clustering

  • André Collignon
  • Dirk Vandermeulen
  • Paul Suetens
  • Guy Marchal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 905)

Abstract

In this paper, 3D voxel-similarity-based (VB) registration algorithms that optimize a feature-space clustering measure are proposed to combine the segmentation and registration process. We present a unifying definition and a classification scheme for existing VB matching criteria and propose a new matching criterion: the entropy of the grey-level scatter-plot. This criterion requires no segmentation or feature extraction and no a priori knowledge of photometric model parameters. The effects of practical implementation issues concerning grey-level resampling, scatter-plot binning, parzen-windowing and resampling frequencies are discussed in detail and evaluated using real world data (CT and MRI).

Keywords

Registration Algorithm Match Criterion Image Grid Neighbour Interpolation Trilinear Interpolation 
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 1995

Authors and Affiliations

  • André Collignon
    • 1
    • 2
    • 3
  • Dirk Vandermeulen
    • 1
    • 2
    • 3
  • Paul Suetens
    • 1
    • 2
    • 3
  • Guy Marchal
    • 1
    • 2
    • 3
  1. 1.Laboratory for Medical Imaging ResearchKatholieke UniversiteitLeuvenBelgium
  2. 2.Department of Electrical EngineeringESATHeverleeBelgium
  3. 3.Department of RadiologyUniversity Hospital GasthuisbergLeuvenBelgium

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