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Improving Registration Using Multi-channel Diffeomorphic Demons Combined with Certainty Maps

  • Daniel Forsberg
  • Yogesh Rathi
  • Sylvain Bouix
  • Demian Wassermann
  • Hans Knutsson
  • Carl-Fredrik Westin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7012)

Abstract

The number of available imaging modalities increases both in clinical practice and in clinical studies. Even though data from multiple modalities might be available, image registration is typically only performed using data from a single modality. In this paper, we propose using certainty maps together with multi-channel diffeomorphic demons in order to improve both accuracy and robustness when performing image registration. The proposed method is evaluated using DTI data, multiple region overlap measures and a fiber bundle similarity metric.

Keywords

Fractional Anisotropy Image Registration Demon Algorithm Womens Hospital 144x144 Encode 
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 2011

Authors and Affiliations

  • Daniel Forsberg
    • 1
    • 2
    • 3
  • Yogesh Rathi
    • 4
  • Sylvain Bouix
    • 4
  • Demian Wassermann
    • 4
  • Hans Knutsson
    • 2
    • 3
  • Carl-Fredrik Westin
    • 5
  1. 1.Sectra ImtecLinköpingSweden
  2. 2.Department of Biomedical EngineeringLinköping UniversitySweden
  3. 3.Center for Medical Image Science and Visualization (CMIV)Linköping UniversitySweden
  4. 4.Psychiatry Neuroimaging Laboratory, Brigham and Womens HospitalHarvard Medical SchoolBostonUSA
  5. 5.Laboratory of Mathematics in Imaging, Brigham and Womens HospitalHarvard Medical SchoolBostonUSA

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