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ECCV
2006
Springer

SIFT and Shape Context for Feature-Based Nonlinear Registration of Thoracic CT Images

11 years 10 months ago
SIFT and Shape Context for Feature-Based Nonlinear Registration of Thoracic CT Images
Nonlinear image registration is a prerequisite for various medical image analysis applications. Many data acquisition protocols suffer from problems due to breathing motion which has to be taken into account for further analysis. Intensity based nonlinear registration is often used to align differing images, however this requires a large computational effort, is sensitive to intensity variations and has problems with matching small structures. In this work a feature-based image registration method is proposed that combines runtime efficiency with good registration accuracy by making use of a fully automatic feature matching and registration approach. The algorithm stages are 3D corner detection, calculation of local (SIFT) and global (Shape Context) 3D descriptors, robust feature matching and calculation of a dense displacement field. An evaluation of the algorithm on seven synthetic and four clinical data sets is presented. The quantitative and qualitative evaluations show lower runti...
Martin Urschler, Joachim Bauer, Hendrik Ditt, Hors
Added 22 Aug 2010
Updated 22 Aug 2010
Type Conference
Year 2006
Where ECCV
Authors Martin Urschler, Joachim Bauer, Hendrik Ditt, Horst Bischof
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