Marker-Less Reconstruction of Dense 4-D Surface Motion Fields Using Active Laser Triangulation for Respiratory Motion Management

  • Sebastian Bauer
  • Benjamin Berkels
  • Svenja Ettl
  • Oliver Arold
  • Joachim Hornegger
  • Martin Rumpf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7510)

Abstract

To manage respiratory motion in image-guided interventions a novel sparse-to-dense registration approach is presented. We apply an emerging laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3-D measurements in real-time. These sparse position measurements are registered with a dense reference surface extracted from planning data. Thereby a dense displacement field is reconstructed which describes the 4-D deformation of the complete patient body surface and recovers a multi-dimensional respiratory signal for application in respiratory motion management. The method is validated on real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured light scanner. In a study on 16 subjects, the proposed algorithm achieved a mean reconstruction accuracy of ±0.22 mm w.r.t. ground truth data.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sebastian Bauer
    • 1
  • Benjamin Berkels
    • 3
  • Svenja Ettl
    • 2
  • Oliver Arold
    • 2
  • Joachim Hornegger
    • 1
  • Martin Rumpf
    • 4
  1. 1.Dept. of Computer SciencePattern Recognition LabGermany
  2. 2.Institute of Optics, Information and PhotonicsFriedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany
  3. 3.Interdisciplinary Mathematics InstituteUniversity of South CarolinaColumbiaUSA
  4. 4.Institute for Numerical SimulationRheinische Friedrich-Wilhelms-Universität BonnBonnGermany

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