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Geodesic Information Flows

  • M. Jorge Cardoso
  • Robin Wolz
  • Marc Modat
  • Nick C. Fox
  • Daniel Rueckert
  • Sebastien Ourselin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7511)

Abstract

Homogenising the availability of manually generated information in large databases has been a key challenge of medical imaging for many years. Due to the time consuming nature of manually segmenting, parcellating and localising landmarks in medical images, these sources of information tend to be scarce and limited to small, and sometimes morphologically similar, subsets of data. In this work we explore a new framework where these sources of information can be propagated to morphologically dissimilar images by diffusing and mapping the information through intermediate steps. The spatially variant data embedding uses the local morphology and intensity similarity between images to diffuse the information only between locally similar images. This framework can thus be used to propagate any information from any group of subject to every other subject in a database with great accuracy. Comparison to state-of-the-art propagation methods showed highly statistically significant (p < 10− 4) improvements in accuracy when propagating both structural parcelations and brain segmentations geodesically.

Keywords

Mild Cognitive Impairment Young Control Neighbourhood Graph Manifold Structure Geodesic Path 
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 2012

Authors and Affiliations

  • M. Jorge Cardoso
    • 1
  • Robin Wolz
    • 2
  • Marc Modat
    • 1
  • Nick C. Fox
    • 3
  • Daniel Rueckert
    • 2
  • Sebastien Ourselin
    • 1
    • 3
  1. 1.Centre for Medical Image Computing (CMIC)University College LondonUK
  2. 2.Visual Information Processing GroupImperial College LondonUK
  3. 3.Dementia Research Centre (DRC)University College LondonUK

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