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Intra-patient Non-rigid Registration of 3D Vascular Cerebral Images

  • David Robben
  • Dirk Smeets
  • Danny Ruijters
  • McElory Hoffmann
  • Laura Antanas
  • Frederik Maes
  • Paul Suetens
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7761)

Abstract

Accuracy of intensity-based non-rigid registration of vascular images is deteriorated in the presence of excessive noise as occurring in CBCT angiography. A new approach to non-rigid registration of vascular images is presented based on the assumption of isometric deformation of vessel structures. For every voxel in the vascular image, the distances along the vessels to some reference voxels are computed as features that are invariant under isometric deformation. Due to the global information on vessel connectivity that is encoded in these features, voxel-based registration of these feature images can compensate for local optima in direct intensity-based registration of the vascular images. The method is validated in the context of brain-shift mitigation, but the technique can be used more broadly. Tests on artificially deformed vascular images show that our algorithm reaches higher accuracy than traditional intensity-based registration.

Keywords

Weighted Distance Vascular Image Brain Shift Minimal Cost Path Gaussian Pyramid 
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 2013

Authors and Affiliations

  • David Robben
    • 1
    • 2
  • Dirk Smeets
    • 1
  • Danny Ruijters
    • 3
  • McElory Hoffmann
    • 2
    • 4
  • Laura Antanas
    • 2
  • Frederik Maes
    • 1
  • Paul Suetens
    • 1
  1. 1.iMinds - Medical Image Computing (ESAT/PSI)KU LeuvenBelgium
  2. 2.Departement ComputerwetenschappenKU LeuvenBelgium
  3. 3.Philips HealthcareThe Netherlands
  4. 4.Department Mathematical SciencesStellenbosch UniversitySouth Africa

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