A unified framework for segmentation-assisted image registration

Authors:
Jundong Liu;Yang Wang;Junhong Liu
Affiliations:
School of Electrical Engineering and Computer Science, Ohio University, Athens, OH;School of Electrical Engineering and Computer Science, Ohio University, Athens, OH;Nokia Inc., Irving, TX
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Year:
2006

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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.