Title
SIFT and shape context for feature-based nonlinear registration of thoracic CT images
Abstract
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 runtime and superior results when compared to the Demons algorithm.
Year
DOI
Venue
2006
10.1007/11889762_7
CVAMIA
Keywords
Field
DocType
feature-based nonlinear registration,automatic feature matching,various medical image analysis,thoracic ct image,good registration accuracy,demons algorithm,feature-based image registration method,registration approach,shape context,nonlinear image registration,robust feature matching,algorithm stage,nonlinear registration,data acquisition,image registration,corner detection
Scale-invariant feature transform,Data set,Feature detection (computer vision),Corner detection,Computer science,Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Shape context,Computer vision,Pattern recognition,Data acquisition,Image registration,Machine learning
Conference
Volume
ISSN
ISBN
4241
0302-9743
3-540-46257-0
Citations 
PageRank 
References 
17
0.83
12
Authors
4
Name
Order
Citations
PageRank
Martin Urschler134723.94
Joachim Bauer2412.40
Hendrik Ditt3262.96
Horst Bischof48751541.43