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High Accuracy Optical Flow for 3D Medical Image Registration Using the Census Cost Function

  • Simon Hermann
  • René Werner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)

Abstract

In 2004, Brox et al. described how to minimize an energy functional for dense 2D optical flow estimation that enforces both intensity and gradient constancy.

This paper presents a novel variant of their method, in which the census cost function is utilized in the data term instead of absolute intensity differences. The algorithm is applied to the task of pulmonary motion estimation in 3D computed tomography (CT) image sequences. The performance evaluation is based on DIR-lab benchmark data for lung CT registration. Results show that the presented algorithm can compete with current state-of-the-art methods in regards to both registration accuracy and run-time.

Keywords

Medical image registration census cost function pulmonary motion estimation 4D CT gradient constancy 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Simon Hermann
    • 1
    • 2
  • René Werner
    • 3
  1. 1.Department of Computer ScienceThe University of AucklandNew Zealand
  2. 2.Department of Computer ScienceHumboldt University of BerlinGermany
  3. 3.Department of Computational NeuroscienceUniversity Medical Center Hamburg-EppendorfGermany

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