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Active Shape and Appearance Models

  • T. F. CootesEmail author
  • M. G. Roberts
  • K. O. Babalola
  • C. J. Taylor

Abstract

Statistical models of shape and appearance are powerful tools for medical image analysis. The shape models can capture the mean and variation in shape of a structure or set of structures across a population. They can be used to help interpret new images by finding the parameters which best match an instance of the model to the image. Two widely used methods for matching are the Active Shape Model and the Active Appearance Model. We describe the models and the matching algorithms, and give examples of their use.

Keywords

Shape Model Model Point Active Appearance Model Statistical Shape Model Triplet Model 
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.

Notes

Acknowledgements

We would like to thank all our colleagues in the Centre for Imaging Sciences for their help. The work was funded by the EPSRC, the MRC and the Arthritis Research Campaign.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • T. F. Cootes
    • 1
    Email author
  • M. G. Roberts
    • 2
  • K. O. Babalola
    • 3
  • C. J. Taylor
    • 4
  1. 1.Centre for Imaging SciencesUniversity of Manchester Stopford BuildingManchesterEngland
  2. 2.Institute of Population Health SciencesUniversity of ManchesterManchesterUK
  3. 3.Manchester Metropolitan UniversityManchesterUK
  4. 4.University of ManchesterManchesterUK

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