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A Unified Framework for Segmentation-Assisted Image Registration

  • Jundong Liu
  • Yang Wang
  • Junhong Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3852)

Abstract

This paper presents a unified variational framework for seamlessly integrating prior segmentation information into non-rigid registration procedures. Under this framework, in addition to the forces arise from the similarity measure in seeking for detailed correspondence, another set of forces generated by the prior segmentation contours can provide an extra guidance in assisting the alignment process towards a more meaningful, stable and noise-tolerant procedure. Local correlation (LC) is being used as the underlying similarity measures to handle intensity variations. We present several 2D/3D examples on synthetic and real data.

Keywords

Mutual Information Image Registration Local Correlation Variational Framework Medical Image Analysis 
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 2006

Authors and Affiliations

  • Jundong Liu
    • 1
  • Yang Wang
    • 1
  • Junhong Liu
    • 2
  1. 1.School of Electrical Engineering and Computer ScienceOhio UniversityAthensUSA
  2. 2.Nokia Inc.IrvingUSA

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