Registration of PET and MR Hand Volumes Using Bayesian Networks

  • Derek Magee
  • Steven Tanner
  • Michael Waller
  • Dennis McGonagle
  • Alan P. Jeavons
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3765)


A method for the non-rigid, multi-modal, registration of volumetric scans of human hands is presented. PET and MR scans are aligned by optimising the configuration of a tube based model using a set of Bayesian networks. Efficient optimisation is performed by posing the problem as a multi-scale, local, discrete (quantised) search, and using dynamic programming. The method is to be used within a project to study the use of high-resolution HIDAC PET imagery in investigating bone growth and erosion in arthritis.


Bayesian Network Positron Emission Tomography Imaging Magnetic Reso Visual Tracking Positron Emission Tomography Data 
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 2005

Authors and Affiliations

  • Derek Magee
    • 1
  • Steven Tanner
    • 1
  • Michael Waller
    • 2
  • Dennis McGonagle
    • 2
  • Alan P. Jeavons
    • 1
  1. 1.School of Computing/Academic Unit of Medical PhysicsUniversity of LeedsUK
  2. 2.Leeds Teaching Hospitals NHS TrustLeedsUK

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