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Publication Detail
Information theoretic similarity measures in non-rigid registration
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Crum WR, Hill DL, Hawkes DJ
  • Publication date:
  • Pagination:
    378, 387
  • Journal:
  • Volume:
  • Issue:
    011-2499 (Print)
  • Keywords:
    Algorithms, Brain, anatomy & histology, Comparative Study, Computer Simulation, Elasticity, Humans, Image Enhancement, methods, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Information Theory, Magnetic Resonance Imaging, Models, Biological, Statistical, Pattern Recognition, Automated, Reproducibility of Results, Research Support, Non-U.S.Gov't, Sensitivity and Specificity, Subtraction Technique
  • Addresses:
    Division of Imaging Sciences, The Guy's, King's and St Thomas' School of Medicine, Guy's Hospital, London SE1 9RT,UK. bill.crum@kcl.ac.uk
  • Notes:
    DA - 20040903
Mutual Information (MI) and Normalised Mutual Information (NMI) have enjoyed success as image similarity measures in medical image registration. More recently, they have been used for non-rigid registration, most often evaluated empirically as functions of changing registration parameter. In this paper we present expressions derived from intensity histogram representations of these measures, for their change in response to a local perturbation of a deformation field linking two images. These expressions give some insight into the operation of NMI in registration and are implemented as driving forces within a fluid registration framework. The performance of the measures is tested on publicly available simulated multi-spectral MR brain images
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